You've already forked lazarus-ccr
LazStats: Massive refactoring of LSMRegUnit re-using general regression routines.
git-svn-id: https://svn.code.sf.net/p/lazarus-ccr/svn@7782 8e941d3f-bd1b-0410-a28a-d453659cc2b4
This commit is contained in:
wp_xxyyzz
@ -49,6 +49,11 @@
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<DebugInfoType Value="dsDwarf2Set"/>
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<TrashVariables Value="True"/>
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</Debugging>
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<Options>
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<Win32>
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<GraphicApplication Value="True"/>
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</Win32>
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</Options>
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</Linking>
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</CompilerOptions>
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</Item2>
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@ -50,9 +50,9 @@ inherited LSMregForm: TLSMregForm
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AnchorSideTop.Control = Label1
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AnchorSideTop.Side = asrBottom
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AnchorSideRight.Control = AllBtn
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AnchorSideBottom.Control = InProb
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AnchorSideBottom.Control = InProbEdit
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Left = 0
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Height = 203
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Height = 182
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Top = 17
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Width = 173
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Anchors = [akTop, akLeft, akRight, akBottom]
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@ -69,7 +69,7 @@ inherited LSMregForm: TLSMregForm
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AnchorSideLeft.Control = AllBtn
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AnchorSideLeft.Side = asrCenter
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AnchorSideTop.Control = VarList
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AnchorSideRight.Control = DepVar
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AnchorSideRight.Control = DepVarEdit
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Left = 187
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Height = 26
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Top = 17
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@ -81,7 +81,7 @@ inherited LSMregForm: TLSMregForm
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TabOrder = 1
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end
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object Label2: TLabel[8]
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AnchorSideLeft.Control = DepVar
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AnchorSideLeft.Control = DepVarEdit
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AnchorSideTop.Control = DepInBtn
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Left = 227
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Height = 15
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@ -91,7 +91,7 @@ inherited LSMregForm: TLSMregForm
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Caption = 'Dependent Variable'
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ParentColor = False
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end
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object DepVar: TEdit[9]
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object DepVarEdit: TEdit[9]
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AnchorSideLeft.Control = IndepVars
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AnchorSideTop.Control = Label2
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AnchorSideTop.Side = asrBottom
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@ -106,7 +106,7 @@ inherited LSMregForm: TLSMregForm
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BorderSpacing.Bottom = 12
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ReadOnly = True
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TabOrder = 3
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Text = 'DepVar'
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Text = 'DepVarEdit'
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end
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object Label3: TLabel[10]
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AnchorSideLeft.Control = IndepVars
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@ -122,11 +122,11 @@ inherited LSMregForm: TLSMregForm
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end
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object Label5: TLabel[11]
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AnchorSideLeft.Control = ParamsPanel
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AnchorSideTop.Control = InProb
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AnchorSideTop.Control = InProbEdit
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AnchorSideTop.Side = asrCenter
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Left = 0
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Height = 15
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Top = 232
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Top = 211
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Width = 192
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BorderSpacing.Right = 8
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Caption = 'Minimum probability to enter block:'
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@ -138,8 +138,8 @@ inherited LSMregForm: TLSMregForm
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AnchorSideRight.Side = asrBottom
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AnchorSideBottom.Control = ButtonBevel
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Left = 0
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Height = 114
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Top = 259
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Height = 135
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Top = 238
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Width = 404
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Anchors = [akLeft, akBottom]
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AutoSize = True
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@ -151,72 +151,80 @@ inherited LSMregForm: TLSMregForm
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ChildSizing.VerticalSpacing = 2
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ChildSizing.Layout = cclLeftToRightThenTopToBottom
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ChildSizing.ControlsPerLine = 2
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ClientHeight = 94
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ClientHeight = 115
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ClientWidth = 400
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TabOrder = 9
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object CPChkBox: TCheckBox
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object ANOVAChk: TCheckBox
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Left = 12
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Height = 19
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Top = 6
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Width = 198
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Caption = 'Show ANOVA'
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TabOrder = 0
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end
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object CrossProductsChk: TCheckBox
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Left = 218
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Height = 19
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Top = 6
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Width = 170
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Caption = 'Show Cross-Products Matrix'
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TabOrder = 0
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end
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object CovChkBox: TCheckBox
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Left = 190
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Height = 19
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Top = 6
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Width = 198
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Caption = 'Show Variance-Covariance Matrix'
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TabOrder = 1
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end
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object CorrsChkBox: TCheckBox
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object CovChk: TCheckBox
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Left = 12
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Height = 19
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Top = 27
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Width = 198
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Caption = 'Show Variance-Covariance Matrix'
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TabOrder = 2
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end
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object CorrsChk: TCheckBox
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Left = 218
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Height = 19
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Top = 27
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Width = 170
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Caption = 'Show Intercorrelation Matrix'
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TabOrder = 2
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end
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object MeansChkBox: TCheckBox
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Left = 190
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Height = 19
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Top = 27
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Width = 198
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Caption = 'Show Means'
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TabOrder = 3
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end
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object VarChkBox: TCheckBox
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object MeansChk: TCheckBox
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Left = 12
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Height = 19
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Top = 48
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Width = 198
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Caption = 'Show Means'
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TabOrder = 4
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end
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object VarChk: TCheckBox
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Left = 218
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Height = 19
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Top = 48
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Width = 170
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Caption = 'Show Variances'
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TabOrder = 4
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end
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object StdDevChkBox: TCheckBox
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Left = 190
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Height = 19
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Top = 48
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Width = 198
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Caption = 'Show Standard Deviations'
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TabOrder = 5
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end
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object MatSaveChkBox: TCheckBox
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object StdDevChk: TCheckBox
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Left = 12
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Height = 19
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Top = 69
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Width = 198
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Caption = 'Show Standard Deviations'
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TabOrder = 6
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end
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object MatSaveChk: TCheckBox
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Left = 218
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Height = 19
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Top = 69
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Width = 170
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Caption = 'Save Correlation Matrix'
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TabOrder = 6
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TabOrder = 7
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end
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object PredictChkBox: TCheckBox
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Left = 190
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object PredictChk: TCheckBox
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Left = 12
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Height = 19
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Top = 69
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Top = 90
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Width = 198
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Caption = 'Predictions,residuals,C.I.''s to Grid'
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TabOrder = 7
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TabOrder = 8
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end
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end
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object IndepVars: TListBox[13]
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@ -229,7 +237,7 @@ inherited LSMregForm: TLSMregForm
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AnchorSideBottom.Control = VarList
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AnchorSideBottom.Side = asrBottom
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Left = 227
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Height = 98
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Height = 77
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Top = 122
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Width = 174
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Anchors = [akTop, akLeft, akRight, akBottom]
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@ -290,21 +298,21 @@ inherited LSMregForm: TLSMregForm
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Spacing = 0
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TabOrder = 5
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end
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object InProb: TEdit[17]
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object InProbEdit: TEdit[17]
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AnchorSideLeft.Control = Label5
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AnchorSideLeft.Side = asrBottom
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AnchorSideRight.Side = asrBottom
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AnchorSideBottom.Control = OptionsGroup
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Left = 200
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Height = 23
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Top = 228
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Top = 207
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Width = 50
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Alignment = taRightJustify
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Anchors = [akLeft, akBottom]
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BorderSpacing.Top = 8
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BorderSpacing.Right = 8
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TabOrder = 8
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Text = 'InProb'
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Text = 'InProbEdit'
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end
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object AllBtn: TBitBtn[18]
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AnchorSideLeft.Control = ParamsPanel
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@ -331,19 +339,22 @@ inherited LSMregForm: TLSMregForm
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Height = 414
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Top = 8
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Width = 580
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ActivePage = MeanVarStddevPage
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ActivePage = RegressionPage
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Align = alClient
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BorderSpacing.Left = 4
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BorderSpacing.Top = 8
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BorderSpacing.Right = 8
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BorderSpacing.Bottom = 8
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TabIndex = 4
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TabIndex = 0
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TabOrder = 2
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object RegressionPage: TTabSheet
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Caption = 'Regression'
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end
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object ANOVAPage: TTabSheet
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Caption = 'ANOVA'
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end
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object CrossProductsPage: TTabSheet
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Caption = 'Cross-Products Matrix'
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Caption = 'Cross-Products'
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end
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object VarCovarPage: TTabSheet
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Caption = 'Variance-Covariance'
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@ -355,8 +366,4 @@ inherited LSMregForm: TLSMregForm
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Caption = 'Mean, Variance, StdDev'
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end
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end
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object SaveDialog: TSaveDialog[3]
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Left = 45
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Top = 357
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end
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end
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@ -7,7 +7,7 @@ interface
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uses
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Classes, SysUtils, FileUtil, Forms, Controls, Graphics, Dialogs,
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StdCtrls, Buttons, ExtCtrls, ComCtrls, Globals, MainUnit, MatrixLib,
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DataProcs, DictionaryUnit, BasicStatsParamsFormUnit, ReportFrameUnit;
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DataProcs, BasicStatsParamsFormUnit, ReportFrameUnit, RegressionUnit;
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type
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@ -15,33 +15,34 @@ type
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TLSMregForm = class(TBasicStatsParamsForm)
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AllBtn: TBitBtn;
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ANOVAChk: TCheckBox;
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IndepVars: TListBox;
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CorrsChkBox: TCheckBox;
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CovChkBox: TCheckBox;
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CPChkBox: TCheckBox;
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CorrsChk: TCheckBox;
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CovChk: TCheckBox;
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CrossProductsChk: TCheckBox;
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DepInBtn: TBitBtn;
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DepOutBtn: TBitBtn;
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DepVar: TEdit;
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DepVarEdit: TEdit;
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OptionsGroup: TGroupBox;
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InBtn: TBitBtn;
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InProb: TEdit;
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InProbEdit: TEdit;
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Label1: TLabel;
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Label2: TLabel;
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Label3: TLabel;
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Label5: TLabel;
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MatSaveChkBox: TCheckBox;
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MeansChkBox: TCheckBox;
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MatSaveChk: TCheckBox;
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MeansChk: TCheckBox;
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PageControl: TPageControl;
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SaveDialog: TSaveDialog;
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OutBtn: TBitBtn;
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PredictChkBox: TCheckBox;
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StdDevChkBox: TCheckBox;
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PredictChk: TCheckBox;
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StdDevChk: TCheckBox;
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RegressionPage: TTabSheet;
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CrossProductsPage: TTabSheet;
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CorrelationsPage: TTabSheet;
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MeanVarStddevPage: TTabSheet;
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ANOVAPage: TTabSheet;
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VarCovarPage: TTabSheet;
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VarChkBox: TCheckBox;
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VarChk: TCheckBox;
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VarList: TListBox;
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procedure AllBtnClick(Sender: TObject);
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procedure DepInBtnClick(Sender: TObject);
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@ -51,9 +52,11 @@ type
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procedure OutBtnClick(Sender: TObject);
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procedure VarListDblClick(Sender: TObject);
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procedure VarListSelectionChange(Sender: TObject; {%H-}User: boolean);
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private
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{ private declarations }
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FRegressionFrame: TReportFrame;
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FAnovaFrame: TReportFrame;
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FCrossProductsFrame: TReportFrame;
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FCorrelationsFrame: TReportFrame;
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FVarCovarFrame: TReportFrame;
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@ -61,11 +64,31 @@ type
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IndepVarsCols: IntDyneVec;
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NoVars: integer;
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NoBlocks: integer;
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procedure HideTabs;
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procedure PredictionToGrid(xData: DblDyneMat; yData: DblDyneVec;
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const ARegressionResults: TMultipleRegressionResults; ABadRows: IntDyneVec);
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function PrepareData(out AIndepCols: IntDyneVec; out ADepCol: Integer;
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out ARowLabels: StrDyneVec; out xValues: DblDyneMat;
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out yValues: DblDyneVec; out ABadRows: IntDyneVec): Boolean;
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procedure Process_Regression(
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const ARowLabels: StrDyneVec; const xValues: DblDyneMat;
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const yValues: DblDyneVec; const ABadRows: IntDyneVec);
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procedure WriteMeanVarStddevReport(AReport: TStrings; AVarNames: StrDyneVec;
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const AMeans, AVars, AStdDevs: DblDyneVec; Flags: Integer);
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procedure WriteReportHeader(AReport: TStrings; AVarNames: StrDyneVec);
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protected
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procedure AdjustConstraints; override;
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procedure Compute; override;
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procedure UpdateBtnStates; override;
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function Validate(out AMsg: String; out AControl: TWinControl): Boolean; override;
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public
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constructor Create(AOwner: TComponent); override;
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procedure Reset; override;
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@ -80,8 +103,8 @@ implementation
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{$R *.lfm}
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uses
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Math,
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Utils, MathUnit;
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Math, StrUtils,
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Utils, GridProcs, MathUnit, MatrixUnit;
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{ TLSMregForm }
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@ -100,6 +123,16 @@ begin
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FRegressionFrame.BorderSpacing.Right := 0;
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InitToolbar(FRegressionFrame.ReportToolbar, tpRight);
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FAnovaFrame := TReportFrame.Create(self);
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FAnovaFrame.Name := '';
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FAnovaFrame.Parent := AnovaPage;
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FAnovaFrame.Align := alClient;
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FAnovaFrame.BorderSpacing.Left := 0;
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FAnovaFrame.BorderSpacing.Top := 0;
|
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FAnovaFrame.BorderSpacing.Bottom := 0;
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FAnovaFrame.BorderSpacing.Right := 0;
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InitToolbar(FAnovaFrame.ReportToolbar, tpRight);
|
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|
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FCrossProductsFrame := TReportFrame.Create(self);
|
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FCrossProductsFrame.Name := '';
|
||||
FCrossProductsFrame.Parent := CrossProductsPage;
|
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@ -151,7 +184,7 @@ begin
|
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4*CloseBtn.Width + 3*CloseBtn.BorderSpacing.Left
|
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);
|
||||
ParamsPanel.Constraints.MinHeight := AllBtn.Top + AllBtn.Height +
|
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VarList.BorderSpacing.Bottom + InProb.Height +
|
||||
VarList.BorderSpacing.Bottom + InProbEdit.Height +
|
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OptionsGroup.BorderSpacing.Top + OptionsGroup.Height +
|
||||
ButtonBevel.Height + CloseBtn.BorderSpacing.Top + CloseBtn.Height;
|
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end;
|
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@ -168,234 +201,17 @@ begin
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||||
end;
|
||||
|
||||
|
||||
procedure TLSMregForm.Compute;
|
||||
procedure TLSMRegForm.Compute;
|
||||
var
|
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i, j, NCases: integer;
|
||||
NoIndepVars, DepVarCol, NEntered: integer;
|
||||
R2, df1, df2: double;
|
||||
StdErrEst, F, FProbF, OldR2: double;
|
||||
pdf1, probin, prout: double;
|
||||
errorcode: boolean;
|
||||
BetaWeights: DblDyneVec = nil;
|
||||
BWeights: DblDyneVec = nil;
|
||||
BStdErrs: DblDyneVec = nil;
|
||||
Bttests: DblDyneVec = nil;
|
||||
tProbs: DblDyneVec = nil;
|
||||
cellstring: string;
|
||||
corrs: DblDyneMat = nil;
|
||||
Means: DblDyneVec = nil;
|
||||
Variances: DblDyneVec = nil;
|
||||
StdDevs: DblDyneVec = nil;
|
||||
title: string;
|
||||
IndRowLabels: StrDyneVec = nil;
|
||||
IndColLabels: StrDyneVec = nil;
|
||||
IndepInverse: DblDyneMat = nil;
|
||||
ColEntered: IntDyneVec = nil;
|
||||
filename: string;
|
||||
constant: double;
|
||||
errcode: boolean = false;
|
||||
anerror: Integer = 0;
|
||||
lReport: TStrings;
|
||||
|
||||
procedure AddHeaderToReport;
|
||||
begin
|
||||
lReport.Clear;
|
||||
lReport.Add('LEAST SQUARES MULTIPLE REGRESSION by Bill Miller');
|
||||
lReport.Add('');
|
||||
end;
|
||||
|
||||
indepCols: IntDyneVec = nil;
|
||||
RowLabels: StrDyneVec = nil;
|
||||
xValues: DblDyneMat = nil;
|
||||
yValues: DblDyneVec = nil;
|
||||
badRows: IntDyneVec = nil;
|
||||
depCol: Integer;
|
||||
begin
|
||||
NCases := NoCases;
|
||||
SetLength(corrs,NoVariables+1,NoVariables+1);
|
||||
SetLength(IndepInverse,NoVariables,NoVariables+1);
|
||||
SetLength(IndepVarsCols,NoVariables+1);
|
||||
SetLength(BWeights,NoVariables+1);
|
||||
SetLength(BStdErrs,NoVariables+1);
|
||||
SetLength(Bttests,NoVariables+1);
|
||||
SetLength(tProbs,NoVariables+1);
|
||||
SetLength(Means,NoVariables+1);
|
||||
SetLength(Variances,NoVariables+1);
|
||||
SetLength(StdDevs,NoVariables+1);
|
||||
SetLength(IndepVarsCols,NoVariables+1);
|
||||
SetLength(IndColLabels,NoVariables+1);
|
||||
SetLength(IndRowLabels,NoVariables+1);
|
||||
SetLength(BetaWeights,NoVariables+1);
|
||||
SetLength(ColEntered,NoVariables+2);
|
||||
|
||||
probin := StrToFloat(InProb.Text); // probability to include a block
|
||||
prout := 1.0;
|
||||
|
||||
if DepVar.Text = '' then
|
||||
begin
|
||||
ErrorMsg('No dependent variable selected.');
|
||||
exit;
|
||||
end;
|
||||
if IndepVars.Items.Count = 0 then
|
||||
begin
|
||||
ErrorMsg('No independent variable selected.');
|
||||
exit;
|
||||
end;
|
||||
|
||||
lReport := TStringList.Create;
|
||||
try
|
||||
errorcode := false;
|
||||
|
||||
{ get dependendent variable column }
|
||||
DepVarCol := 0;
|
||||
NoVars := NoVars + 1;
|
||||
for j := 1 to NoVariables do
|
||||
if DepVar.Text = OS3MainFrm.DataGrid.Cells[j,0] then DepVarCol := j;
|
||||
|
||||
R2 := 0.0;
|
||||
OldR2 := 0.0;
|
||||
pdf1 := 0.0;
|
||||
NEntered := 0;
|
||||
|
||||
{ get independendent variable column }
|
||||
for i := 0 to IndepVars.Count-1 do
|
||||
begin
|
||||
//cellstring := OS3Mainfrm.DataGrid.Cells[i+1,0]; // bug
|
||||
cellstring := IndepVars.Items[i]; //Bugfix by tatamata
|
||||
for j := 1 to NoVariables do
|
||||
begin
|
||||
if cellstring = OS3MainFrm.DataGrid.Cells[j,0] then
|
||||
begin
|
||||
IndepVarsCols[i] := j;
|
||||
ColEntered[i] := j;
|
||||
NEntered := NEntered + 1;
|
||||
IndRowLabels[NEntered-1] := cellstring;
|
||||
IndColLabels[NEntered-1] := cellstring;
|
||||
end;
|
||||
end;
|
||||
end;
|
||||
NEntered := NEntered + 1; // dependent variable last
|
||||
ColEntered[NEntered-1] := DepVarCol;
|
||||
IndRowLabels[NEntered-1] := OS3MainFrm.DataGrid.Cells[DepVarCol,0];
|
||||
IndColLabels[NEntered-1] := OS3MainFrm.DataGrid.Cells[DepVarCol,0];
|
||||
|
||||
if CPChkBox.Checked then
|
||||
begin
|
||||
title := 'Cross-Products Matrix';
|
||||
AddHeaderToReport;
|
||||
GridXProd(NEntered, ColEntered, Corrs, errcode, NCases);
|
||||
MatPrint(Corrs, NEntered, NEntered, title, IndRowLabels, IndColLabels, NCases, lReport);
|
||||
FCrossProductsFrame.DisplayReport(lReport);
|
||||
CrossProductsPage.TabVisible := true;
|
||||
end else
|
||||
CrossProductsPage.TabVisible := false;
|
||||
|
||||
if CovChkBox.Checked then
|
||||
begin
|
||||
title := 'Variance-Covariance Matrix';
|
||||
AddHeaderToReport;
|
||||
GridCovar(NEntered,ColEntered, Corrs, Means, Variances, StdDevs, errcode, NCases);
|
||||
MatPrint(Corrs, NEntered, NEntered, title, IndRowLabels, IndColLabels, NCases, lReport);
|
||||
FVarCovarFrame.DisplayReport(lReport);
|
||||
VarCovarPage.TabVisible := true;
|
||||
// lReport.Add(DIVIDER_SMALL);
|
||||
end;
|
||||
|
||||
Correlations(NEntered,ColEntered,Corrs,Means,Variances, StdDevs,errcode,NCases);
|
||||
if CorrsChkBox.Checked then
|
||||
begin
|
||||
title := 'Product-Moment Correlations Matrix';
|
||||
AddHeaderToReport;
|
||||
MatPrint(Corrs, NEntered, NEntered, title, IndRowLabels, IndColLabels, NCases, lReport);
|
||||
FCorrelationsFrame.DisplayReport(lReport);
|
||||
CorrelationsPage.TabVisible := true;
|
||||
end else
|
||||
CorrelationsPage.TabVisible := false;
|
||||
|
||||
if MeansChkBox.Checked or VarChkBox.Checked or StdDevChkBox.Checked then
|
||||
begin
|
||||
AddHeaderToReport;
|
||||
|
||||
if MeansChkBox.Checked then
|
||||
begin
|
||||
title := 'MEANS';
|
||||
DynVectorPrint(Means, NEntered, title, IndColLabels, NCases, lReport);
|
||||
lReport.Add(DIVIDER_SMALL);
|
||||
lReport.Add('');
|
||||
end;
|
||||
|
||||
if VarChkBox.Checked then
|
||||
begin
|
||||
title := 'VARIANCES';
|
||||
DynVectorPrint(Variances, NEntered, title, IndColLabels, NCases, lReport);
|
||||
lReport.Add(DIVIDER_SMALL);
|
||||
lReport.Add('');
|
||||
end;
|
||||
|
||||
if StdDevChkBox.Checked then
|
||||
begin
|
||||
title := 'STANDARD DEVIATIONS';
|
||||
DynVectorPrint(StdDevs, NEntered, title, IndColLabels, NCases, lReport);
|
||||
lReport.Add(DIVIDER_SMALL);
|
||||
lReport.Add('');
|
||||
end;
|
||||
|
||||
FMeanVarStddevFrame.DisplayReport(lReport);
|
||||
MeanVarStddevPage.TabVisible := true;
|
||||
end else
|
||||
MeanVarStddevPage.TabVisible := false;
|
||||
|
||||
if errorcode then
|
||||
begin
|
||||
ErrorMsg('A selected variable has no variability. Run aborted.');
|
||||
exit;
|
||||
end;
|
||||
NoIndepVars := NEntered - 1;
|
||||
|
||||
AddHeaderToReport;
|
||||
|
||||
MReg(NoIndepVars, ColEntered, DepVarCol, IndRowLabels, Means, Variances,
|
||||
StdDevs, BWeights, BetaWeights, BStdErrs, Bttests, tProbs, R2,
|
||||
StdErrEst, NCases, errorcode, true, lReport);
|
||||
|
||||
df1 := NoIndepVars - pdf1;
|
||||
df2 := NCases - NoIndepVars - 1;
|
||||
F := ((R2 - OldR2) / (1.0 - R2)) * df2 / df1;
|
||||
FProbF := ProbF(F,df1,df2);
|
||||
lReport.Add('');
|
||||
if FProbF < probIn then
|
||||
lReport.Add('Entry requirements met')
|
||||
else
|
||||
lReport.Add('Entry requirements not met');
|
||||
|
||||
lReport.Add('');
|
||||
lReport.Add(DIVIDER);
|
||||
lReport.Add('');
|
||||
|
||||
{ add [predicted scores, residual scores, etc. to grid if options elected }
|
||||
if PredictChkBox.Checked then
|
||||
begin
|
||||
prout := 1.0;
|
||||
Correlations(NEntered, ColEntered, Corrs, Means, Variances, StdDevs, errcode, NCases);
|
||||
|
||||
MReg2(NCases, NEntered, NoIndepVars, ColEntered, corrs, IndepInverse,
|
||||
IndRowLabels, R2, BetaWeights, Means, Variances, anerror,
|
||||
StdErrEst, constant, prout, true, false, false, lReport);
|
||||
|
||||
Predict(ColEntered, NEntered, IndepInverse, Means, StdDevs,
|
||||
BetaWeights, StdErrEst, IndepVarsCols, NoIndepVars);
|
||||
end;
|
||||
|
||||
if MatSaveChkBox.Checked then
|
||||
begin
|
||||
SaveDialog.Filter := 'LazStats matrix files (*.mat)|*.mat;*.MAT|All files (*.*)|*.*';
|
||||
SaveDialog.FilterIndex := 1;
|
||||
if SaveDialog.Execute then
|
||||
begin
|
||||
filename := SaveDialog.FileName;
|
||||
MatSave(Corrs, NoVars, NoVars, Means, StdDevs, NCases, IndRowLabels, IndColLabels, filename);
|
||||
end;
|
||||
end;
|
||||
|
||||
FRegressionFrame.DisplayReport(lReport);
|
||||
|
||||
finally
|
||||
lReport.Free;
|
||||
end;
|
||||
if PrepareData(indepCols, depCol, RowLabels, xValues, yValues, badRows) then
|
||||
Process_Regression(RowLabels, xValues, yValues, badRows);
|
||||
end;
|
||||
|
||||
|
||||
@ -404,9 +220,9 @@ var
|
||||
index: integer;
|
||||
begin
|
||||
index := VarList.ItemIndex;
|
||||
if (index > -1) and (DepVar.Text = '') then
|
||||
if (index > -1) and (DepVarEdit.Text = '') then
|
||||
begin
|
||||
DepVar.Text := VarList.Items[index];
|
||||
DepVarEdit.Text := VarList.Items[index];
|
||||
VarList.Items.Delete(index);
|
||||
end;
|
||||
UpdateBtnStates;
|
||||
@ -415,10 +231,10 @@ end;
|
||||
|
||||
procedure TLSMregForm.DepOutBtnClick(Sender: TObject);
|
||||
begin
|
||||
if DepVar.Text <> '' then
|
||||
if DepVarEdit.Text <> '' then
|
||||
begin
|
||||
VarList.Items.Add(DepVar.Text);
|
||||
DepVar.Text := '';
|
||||
VarList.Items.Add(DepVarEdit.Text);
|
||||
DepVarEdit.Text := '';
|
||||
end;
|
||||
UpdateBtnStates;
|
||||
end;
|
||||
@ -483,6 +299,235 @@ begin
|
||||
UpdateBtnStates;
|
||||
end;
|
||||
|
||||
|
||||
procedure TLSMregForm.PredictionToGrid(xData: DblDyneMat; yData: DblDyneVec;
|
||||
const ARegressionResults: TMultipleRegressionResults; ABadRows: IntDyneVec);
|
||||
var
|
||||
zPred, zResid, rawPred, rawResid, stdErrPred, hi95, lo95: DblDyneVec;
|
||||
begin
|
||||
PredictMR(xData, yData, ARegressionResults,
|
||||
zPred, zResid, RawPred, RawResid, StdErrPred, Hi95, Lo95);
|
||||
|
||||
AddVariable('Pred.z', zPred, '%8.4f', ABadRows);
|
||||
AddVariable('z Resid', zResid, '%8.4f', ABadRows);
|
||||
AddVariable('Raw Pred', rawPred, '%8.3f', ABadRows);
|
||||
AddVariable('Raw Resid', rawResid, '%8.3f', ABadRows);
|
||||
AddVariable('StdErr Pred', stdErrPred, '%8.3f', ABadRows);
|
||||
AddVariable('Low 95%', lo95, '%8.3f', ABadRows);
|
||||
AddVariable('Top 95%', hi95, '%8.3f', ABadRows);
|
||||
end;
|
||||
|
||||
|
||||
{ Prepares the data for the analysis by extracting all needed data from the
|
||||
grid:
|
||||
- AIndepCols: integer array containing the grid column indexes of the
|
||||
independent variables to be used
|
||||
- ADepCol: grid column index of the dependent variable to be used
|
||||
- ARowLabels: string array containing the names of the independent variables
|
||||
as well of the dependent variable (last)
|
||||
- xValues: matrix with all independent values. The columns of the matrix
|
||||
correspond to the variables, the row correspond to the cases.
|
||||
- yValues: vector with the dependent variable values
|
||||
}
|
||||
function TLSMregForm.PrepareData(out AIndepCols: IntDyneVec; out ADepCol: Integer;
|
||||
out ARowLabels: StrDyneVec; out xValues: DblDyneMat; out yValues: DblDyneVec;
|
||||
out ABadRows: IntDyneVec): Boolean;
|
||||
var
|
||||
i, n: Integer;
|
||||
msg: String;
|
||||
C: TWinControl;
|
||||
numIndepCols: Integer;
|
||||
cols: IntDyneVec = nil;
|
||||
begin
|
||||
Result := false;
|
||||
AIndepCols := nil;
|
||||
ARowLabels := nil;
|
||||
xValues := nil;
|
||||
yvalues := nil;
|
||||
ABadRows := nil;
|
||||
|
||||
if not Validate(msg, C) then
|
||||
begin
|
||||
C.SetFocus;
|
||||
ErrorMsg(msg);
|
||||
exit;
|
||||
end;
|
||||
|
||||
numIndepCols := IndepVars.Items.Count;
|
||||
ADepCol := GetVariableIndex(OS3MainFrm.DataGrid, DepVarEdit.Text);
|
||||
|
||||
SetLength(AIndepCols, numIndepCols);
|
||||
SetLength(ARowLabels, numIndepCols + 1); // +1 to add independent column label
|
||||
|
||||
for i := 0 to numIndepCols-1 do
|
||||
begin
|
||||
AIndepCols[i] := GetVariableIndex(OS3MainFrm.DataGrid, IndepVars.Items[i]);
|
||||
if AIndepCols[i] = -1 then
|
||||
begin
|
||||
ErrorMsg('Dependent variable %s not found.', [IndepVars.Items[i]]);
|
||||
exit;
|
||||
end;
|
||||
ARowLabels[i] := IndepVars.Items[i];
|
||||
end;
|
||||
ARowLabels[numIndepCols] := DepVarEdit.Text;
|
||||
|
||||
// Check variable types: all of them must be numeric (float or integer)
|
||||
if not IsNumericCol(ADepCol) then
|
||||
begin
|
||||
ErrorMsg('Incorrect data type of dependent variable.');
|
||||
exit;
|
||||
end;
|
||||
|
||||
for i := 0 to numIndepCols-1 do
|
||||
if not IsNumericCol(AIndepCols[i]) then
|
||||
begin
|
||||
ErrorMsg('Incorrect data type of independent variable "%s"', [ARowLabels[i]]);
|
||||
exit;
|
||||
end;
|
||||
|
||||
// Prepare list of all column indices to be loaded: x, y
|
||||
// ADepCol will follow immediately after the x columns.
|
||||
SetLength(cols, NumIndepCols + 1);
|
||||
cols[numIndepCols] := ADepCol;
|
||||
for i := 0 to numIndepCols-1 do cols[i] := AIndepCols[i];
|
||||
|
||||
// Determine list of indices of rows containing invalid entries.
|
||||
SetLength(ABadRows, OS3MainFrm.DataGrid.RowCount);
|
||||
n := 0;
|
||||
for i := 1 to OS3MainFrm.DataGrid.RowCount-1 do
|
||||
if not GoodRecord(OS3MainFrm.DataGrid, i, cols) then
|
||||
begin
|
||||
ABadRows[n] := i;
|
||||
inc(n);
|
||||
end;
|
||||
SetLength(ABadRows, n);
|
||||
|
||||
// Extract data values; take care to skip invalid values in both x and y
|
||||
xValues := CollectMatValues(OS3MainFrm.DataGrid, cols);
|
||||
// The y column has index numIndepCols, i.e. follows after the x columns.
|
||||
yValues := MatColVector(xValues, numIndepCols);
|
||||
MatColDelete(xValues, numIndepCols);
|
||||
|
||||
Result := true;
|
||||
end;
|
||||
|
||||
|
||||
{ Runs the least squares regression on the data in xValues and yValues }
|
||||
procedure TLSMregForm.Process_Regression(const ARowLabels: StrDyneVec;
|
||||
const xValues: DblDyneMat; const yValues: DblDyneVec;
|
||||
const ABadRows: IntDyneVec);
|
||||
var
|
||||
lReport: TStrings;
|
||||
regressionRes: TMultipleRegressionResults;
|
||||
n: Integer;
|
||||
confLevel: Double;
|
||||
err: TRegressionError;
|
||||
flags: Integer;
|
||||
means: DblDyneVec = nil;
|
||||
vars: DblDyneVec = nil;
|
||||
stdDevs: DblDyneVec = nil;
|
||||
begin
|
||||
confLevel := 1.0 - StrToFloat(InProbEdit.Text);
|
||||
|
||||
err := MultipleRegression(xValues, yValues, confLevel, regressionRes);
|
||||
case err of
|
||||
regOK : ;
|
||||
regTooFewValues : ErrorMsg('At least two values required for regression.');
|
||||
end;
|
||||
if err <> regOK then
|
||||
exit;
|
||||
|
||||
// Calculate means, variances, stddevs of all required variables and put them
|
||||
// in vectors means, vars, stddevs, y data at end.
|
||||
MatColMeanVarStdDev(xValues, means, vars, stdDevs);
|
||||
n := Length(means);
|
||||
SetLength(means, n+1);
|
||||
SetLength(vars, n+1);
|
||||
SetLength(stddevs, n+1);
|
||||
VecMeanVarStdDev(yValues, means[n], vars[n], stddevs[n]);
|
||||
|
||||
lReport := TStringList.Create;
|
||||
try
|
||||
WriteReportHeader(lReport, ARowLabels);
|
||||
regressionRes.WriteCoeffsReport(lReport, ARowLabels);
|
||||
FRegressionFrame.DisplayReport(lReport);
|
||||
|
||||
if AnovaChk.Checked then
|
||||
begin
|
||||
lReport.Clear;
|
||||
WriteReportHeader(lReport, ARowLabels);
|
||||
regressionRes.WriteAnovaReport(lReport);
|
||||
FAnovaFrame.DisplayReport(lReport);
|
||||
end;
|
||||
AnovaPage.TabVisible := AnovaChk.Checked;
|
||||
|
||||
if CrossProductsChk.Checked then
|
||||
begin
|
||||
lReport.Clear;
|
||||
WriteReportHeader(lReport, ARowLabels);
|
||||
regressionRes.WriteCrossProductsReport(lReport, ARowLabels);
|
||||
FCrossProductsFrame.DisplayReport(lReport);
|
||||
end;
|
||||
CrossProductsPage.TabVisible := CrossProductsChk.Checked;
|
||||
|
||||
if CovChk.Checked then
|
||||
begin
|
||||
lReport.Clear;
|
||||
WriteReportHeader(lReport, ARowLabels);
|
||||
regressionRes.WriteVarCovarReport(lReport, ARowLabels);
|
||||
FVarCovarFrame.DisplayReport(lReport);
|
||||
end;
|
||||
VarCovarPage.TabVisible := CovChk.Checked;
|
||||
|
||||
if CorrsChk.Checked then
|
||||
begin
|
||||
lReport.Clear;
|
||||
WriteReportHeader(lReport, ARowLabels);
|
||||
regressionRes.WriteCorrelationReport(lReport, ARowLabels);
|
||||
FCorrelationsFrame.DisplayReport(lReport);
|
||||
end;
|
||||
CorrelationsPage.TabVisible := CorrsChk.Checked;
|
||||
|
||||
if MeansChk.Checked or VarChk.Checked or StdDevChk.Checked then
|
||||
begin
|
||||
lReport.Clear;
|
||||
WriteReportHeader(lReport, ARowLabels);
|
||||
flags := 0;
|
||||
if MeansChk.Checked then inc(flags, 1);
|
||||
if VarChk.Checked then inc(flags, 2);
|
||||
if StdDevChk.Checked then inc(flags, 4);
|
||||
WriteMeanVarStddevReport(lReport, ARowLabels, means, vars, stdDevs, flags);
|
||||
FMeanVarStdDevFrame.displayReport(lReport);
|
||||
end;
|
||||
MeanVarStdDevPage.TabVisible := MeansChk.Checked or VarChk.Checked or StdDevChk.Checked;
|
||||
|
||||
if PredictChk.Checked then
|
||||
PredictionToGrid(xValues, yValues, regressionRes, ABadRows);
|
||||
|
||||
if MatSaveChk.Checked then
|
||||
begin
|
||||
Application.ProcessMessages;
|
||||
with TSaveDialog.Create(nil) do
|
||||
try
|
||||
Filter := 'LazStats matrix files (*.mat)|*.mat;*.MAT|All files (*.*)|*.*';
|
||||
FilterIndex := 1;
|
||||
if Execute then
|
||||
begin
|
||||
n := Length(means);
|
||||
MatSave(RegressionRes.Correlations, n-1, n-1, means, stdDevs, regressionRes.NumCases, ARowLabels, ARowLabels, Filename);
|
||||
end;
|
||||
finally
|
||||
Free;
|
||||
end;
|
||||
MatSaveChk.Checked := false;
|
||||
end;
|
||||
|
||||
finally
|
||||
lReport.Free;
|
||||
end;
|
||||
end;
|
||||
|
||||
|
||||
procedure TLSMregForm.Reset;
|
||||
var
|
||||
i: integer;
|
||||
@ -496,18 +541,19 @@ begin
|
||||
for i := 1 to NoVariables do
|
||||
VarList.Items.Add(OS3MainFrm.DataGrid.Cells[i,0]);
|
||||
|
||||
CPChkBox.Checked := false;
|
||||
CovChkBox.Checked := false;
|
||||
CorrsChkBox.Checked := true;
|
||||
MeansChkBox.Checked := true;
|
||||
VarChkBox.Checked := false;
|
||||
StdDevChkBox.Checked := true;
|
||||
MatSaveChkBox.Checked := false;
|
||||
PredictChkBox.Checked := false;
|
||||
AnovaChk.Checked := true;
|
||||
CrossProductsChk.Checked := false;
|
||||
CovChk.Checked := true;
|
||||
CorrsChk.Checked := true;
|
||||
MeansChk.Checked := true;
|
||||
VarChk.Checked := false;
|
||||
StdDevChk.Checked := true;
|
||||
MatSaveChk.Checked := false;
|
||||
PredictChk.Checked := false;
|
||||
|
||||
NoVars := 0;
|
||||
DepVar.Text := '';
|
||||
InProb.Text := FormatFloat('0.00', DEFAULT_ALPHA_LEVEL);
|
||||
DepVarEdit.Text := '';
|
||||
InProbEdit.Text := FormatFloat('0.00', DEFAULT_ALPHA_LEVEL);
|
||||
SetLength(IndepVarsCols, NoVariables+1);
|
||||
|
||||
HideTabs;
|
||||
@ -523,6 +569,8 @@ begin
|
||||
|
||||
if Assigned(FRegressionFrame) then
|
||||
FRegressionFrame.UpdateBtnStates;
|
||||
if Assigned(FAnovaFrame) then
|
||||
FAnovaFrame.UpdateBtnStates;
|
||||
if Assigned(FCrossProductsFrame) then
|
||||
FCrossProductsFrame.UpdateBtnStates;
|
||||
if Assigned(FCorrelationsFrame) then
|
||||
@ -536,11 +584,48 @@ begin
|
||||
DepInBtn.Enabled := lSelected;
|
||||
InBtn.Enabled := lSelected;
|
||||
OutBtn.Enabled := AnySelected(IndepVars);
|
||||
DepOutBtn.Enabled := DepVar.Text <> '';
|
||||
DepOutBtn.Enabled := DepVarEdit.Text <> '';
|
||||
AllBtn.Enabled := VarList.Items.Count > 0;
|
||||
end;
|
||||
|
||||
|
||||
function TLSMregForm.Validate(out AMsg: String; out AControl: TWinControl): Boolean;
|
||||
var
|
||||
x: double;
|
||||
begin
|
||||
Result := false;
|
||||
|
||||
if DepVarEdit.Text = '' then
|
||||
begin
|
||||
AControl := DepVarEdit;
|
||||
AMsg := 'No dependent variable selected.';
|
||||
exit;
|
||||
end;
|
||||
|
||||
if IndepVars.Items.Count = 0 then
|
||||
begin
|
||||
AControl := IndepVars;
|
||||
AMsg := 'No independent variables selected.';
|
||||
exit;
|
||||
end;
|
||||
|
||||
if InProbEdit.Text = '' then
|
||||
begin
|
||||
AControl := InProbEdit;
|
||||
AMsg := 'This field cannot be empty.';
|
||||
exit;
|
||||
end;
|
||||
if not TryStrToFloat(InProbEdit.Text, x) then
|
||||
begin
|
||||
AControl := InProbEdit;
|
||||
AMsg := 'Non-numeric value.';
|
||||
exit;
|
||||
end;
|
||||
|
||||
Result := true;
|
||||
end;
|
||||
|
||||
|
||||
procedure TLSMregForm.VarListDblClick(Sender: TObject);
|
||||
var
|
||||
index: Integer;
|
||||
@ -548,8 +633,8 @@ begin
|
||||
index := VarList.ItemIndex;
|
||||
if index > -1 then
|
||||
begin
|
||||
if DepVar.Text = '' then
|
||||
DepVar.Text := VarList.Items[index]
|
||||
if DepVarEdit.Text = '' then
|
||||
DepVarEdit.Text := VarList.Items[index]
|
||||
else
|
||||
IndepVars.Items.Add(VarList.Items[index]);
|
||||
VarList.Items.Delete(index);
|
||||
@ -564,5 +649,98 @@ begin
|
||||
end;
|
||||
|
||||
|
||||
{ Flags = 1 ... mean; Flags = 2 ... variacne; Flags = 4 = stdDev }
|
||||
procedure TLSMRegForm.WriteMeanVarStddevReport(AReport: TStrings;
|
||||
AVarNames: StrDyneVec; const AMeans, AVars, AStdDevs: DblDyneVec;
|
||||
Flags: Integer);
|
||||
const
|
||||
W = 15;
|
||||
SPACE = ' ';
|
||||
MASK = SPACE + '%*.3f';
|
||||
var
|
||||
s, sL, sLL: String;
|
||||
i, n: Integer;
|
||||
begin
|
||||
s := '';
|
||||
if Flags and 1 <> 0 then
|
||||
s := s + 'MEANS, ';
|
||||
if Flags and 2 <> 0 then
|
||||
s := s + 'VARIANCES, ';
|
||||
if Flags and 4 <> 0 then
|
||||
s := s + 'STANDARD DEVIATIONS, ';
|
||||
SetLength(s, Length(s)-2); // remove training ', '
|
||||
|
||||
//Caption
|
||||
AReport.Add(s);
|
||||
|
||||
n := 1;
|
||||
s := CenterString('Variable', W);
|
||||
sL := DupeString('-', W);
|
||||
if Flags and 1 <> 0 then
|
||||
begin
|
||||
s := s + SPACE + CenterString('Mean', W);
|
||||
sL := sL + SPACE + Dupestring('-', W);
|
||||
inc(n);
|
||||
end;
|
||||
if Flags and 2 <> 0 then
|
||||
begin
|
||||
s := s + SPACE + CenterString('Variance', W);
|
||||
sL := sL + SPACE + Dupestring('-', W);
|
||||
inc(n);
|
||||
end;
|
||||
if Flags and 4 <> 0 then
|
||||
begin
|
||||
s := s + SPACE + CenterString('Std.Deviation', W);
|
||||
sL := sL + SPACE + Dupestring('-', W);
|
||||
inc(n);
|
||||
end;
|
||||
|
||||
// Divider below caption
|
||||
sLL := DupeString('-', n*W + (n-1) * Length(SPACE));
|
||||
AReport.Add(sLL);
|
||||
|
||||
// Table headers
|
||||
AReport.Add(s);
|
||||
// Table header separating line
|
||||
AReport.Add(sL);
|
||||
|
||||
// Table cells
|
||||
n := Length(AMeans);
|
||||
for i := 0 to n-1 do
|
||||
begin
|
||||
s := Format('%*s', [W, AVarNames[i]]);
|
||||
if Flags and 1 <> 0 then
|
||||
s := s + Format(MASK, [W, AMeans[i]]);
|
||||
if Flags and 2 <> 0 then
|
||||
s := s + Format(MASK, [W, AVars[i]]);
|
||||
if Flags and 4 <> 0 then
|
||||
s := s + Format(MASK, [W, AStdDevs[i]]);
|
||||
AReport.Add(s);
|
||||
if i = n-2 then
|
||||
AReport.Add(sL);
|
||||
end;
|
||||
|
||||
// Final dividing line below table
|
||||
AReport.Add(sLL);
|
||||
end;
|
||||
|
||||
|
||||
procedure TLSMRegForm.WriteReportHeader(AReport: TStrings; AVarNames: StrDyneVec);
|
||||
var
|
||||
i, n: Integer;
|
||||
begin
|
||||
n := Length(AVarNames);
|
||||
AReport.Clear;
|
||||
AReport.Add('LEAST SQUARES REGRESSION RESULTS');
|
||||
AReport.Add('');
|
||||
AReport.Add('Dependent variable: ');
|
||||
AReport.Add(' ' + AVarNames[n-1]);
|
||||
AReport.Add('Independent variables:');
|
||||
for i := 0 to n-2 do
|
||||
AReport.Add(' ' + AVarNames[i]);
|
||||
AReport.Add('');
|
||||
end;
|
||||
|
||||
|
||||
end.
|
||||
|
||||
|
||||
@ -728,9 +728,9 @@ begin
|
||||
end;
|
||||
SetLength(ABadRows, n);
|
||||
|
||||
// Extract data values; take care to omit invalid values in both x and y
|
||||
// Extract data values; take care to skip invalid values in both x and y
|
||||
xValues := CollectMatValues(OS3MainFrm.DataGrid, cols);
|
||||
// The y column has index numIndepCols, i.e. follows the x columns.
|
||||
// The y column has index numIndepCols, i.e. follows after the x columns.
|
||||
yValues := MatColVector(xValues, numIndepCols);
|
||||
MatColDelete(xValues, numIndepCols);
|
||||
if AWeightCol > -1 then
|
||||
|
||||
@ -845,13 +845,13 @@ begin
|
||||
WriteLn(mat_file, NoCols);
|
||||
WriteLn(mat_file, NCases);
|
||||
|
||||
for i := 1 to NoRows do WriteLn(mat_file, RowLabels[i-1]);
|
||||
for i := 1 to NoCols do WriteLn(mat_file, ColLabels[i-1]);
|
||||
for i := 1 to NoCols do WriteLn(mat_file, Means[i-1]);
|
||||
for i := 1 to NoCols do WriteLn(mat_file, StdDevs[i-1]);
|
||||
for i := 1 to NoRows do
|
||||
for j := 1 to NoCols do
|
||||
WriteLn(mat_file, a[i-1, j-1]);
|
||||
for i := 0 to NoRows-1 do WriteLn(mat_file, RowLabels[i]);
|
||||
for i := 0 to NoCols-1 do WriteLn(mat_file, ColLabels[i]);
|
||||
for i := 0 to NoCols-1 do WriteLn(mat_file, Means[i]);
|
||||
for i := 0 to NoCols-1 do WriteLn(mat_file, StdDevs[i]);
|
||||
for i := 0 to NoRows-1 do
|
||||
for j := 0 to NoCols-1 do
|
||||
WriteLn(mat_file, a[i, j]);
|
||||
|
||||
CloseFile(mat_file);
|
||||
end; { matrix save routine }
|
||||
|
||||
@ -6,7 +6,7 @@ interface
|
||||
|
||||
uses
|
||||
Classes, SysUtils, Dialogs,
|
||||
Globals, DictionaryUnit, FunctionsLib, DataProcs, MainUnit;
|
||||
Globals, DictionaryUnit, FunctionsLib, GridProcs, DataProcs, MainUnit;
|
||||
|
||||
//type
|
||||
// TRegItem = (riMeanVarStdDev, riXTX);
|
||||
@ -142,6 +142,9 @@ procedure DynIntMatPrint(Mat: IntDyneMat; Rows, Cols: integer; YTitle: string;
|
||||
procedure SymMatRoots(A : DblDyneMat; M : integer; VAR E : DblDyneVec; VAR V : DblDyneMat);
|
||||
procedure matinv(a, vtimesw, v, w: DblDyneMat; n: integer);
|
||||
|
||||
procedure AddVariable(AVarName: String; AData: DblDyneVec;
|
||||
ANumFormat: String; const ABadRows: IntDyneVec);
|
||||
|
||||
|
||||
implementation
|
||||
|
||||
@ -1113,10 +1116,12 @@ begin
|
||||
DictionaryFrm.NewVar(col);
|
||||
DictionaryFrm.DictGrid.Cells[1,col] := 'Pred.z';
|
||||
OS3MainFrm.DataGrid.Cells[col,0] := 'Pred.z';
|
||||
|
||||
col := NoVariables + 1;
|
||||
DictionaryFrm.NewVar(col);
|
||||
DictionaryFrm.DictGrid.Cells[1,col] := 'z Resid.';
|
||||
OS3MainFrm.DataGrid.Cells[col,0] := 'z Resid.';
|
||||
|
||||
for i := 1 to NoCases do
|
||||
begin
|
||||
zpredicted := 0.0;
|
||||
@ -1134,10 +1139,12 @@ begin
|
||||
z2 := (z2 - Means[NoVars-1]) / StdDevs[NoVars-1];
|
||||
OS3MainFrm.DataGrid.Cells[col,i] := format('%8.4f',[(z2 - zpredicted)]);
|
||||
end;
|
||||
|
||||
col := NoVariables + 1;
|
||||
DictionaryFrm.NewVar(col);
|
||||
DictionaryFrm.DictGrid.Cells[1,col] := 'Pred.Raw';
|
||||
OS3MainFrm.DataGrid.Cells[col,0] := 'Pred.Raw';
|
||||
|
||||
{ calculate raw predicted scores and store in grid at col }
|
||||
for i := 1 to NoCases do
|
||||
begin
|
||||
@ -1145,11 +1152,13 @@ begin
|
||||
StdDevs[NoVars-1] + Means[NoVars-1];
|
||||
OS3MainFrm.DataGrid.Cells[col,i] := format('%8.3f',[predicted]);
|
||||
end;
|
||||
|
||||
{ Calculate residuals of predicted raw scores }
|
||||
col := NoVariables +1;
|
||||
DictionaryFrm.NewVar(col);
|
||||
DictionaryFrm.DictGrid.Cells[1,col] := 'Raw Resid.';
|
||||
OS3MainFrm.DataGrid.Cells[col,0] := 'Raw Resid.';
|
||||
|
||||
for i := 1 to NoCases do
|
||||
begin
|
||||
Index := ColNoSelected[NoVars-1];
|
||||
@ -1157,19 +1166,23 @@ begin
|
||||
StrToFloat(Trim(OS3MainFrm.DataGrid.Cells[Index,i]));
|
||||
OS3MainFrm.DataGrid.Cells[col,i] := Format('%8.3f',[resid]);
|
||||
end;
|
||||
|
||||
{ Calculate Confidence Interval for raw predicted score }
|
||||
col := NoVariables + 1;
|
||||
DictionaryFrm.NewVar(col);
|
||||
DictionaryFrm.DictGrid.Cells[1,col] := 'StdErrPred';
|
||||
OS3MainFrm.DataGrid.Cells[col,0] := 'StdErrPred';
|
||||
|
||||
col := NoVariables + 1;
|
||||
DictionaryFrm.NewVar(col);
|
||||
DictionaryFrm.DictGrid.Cells[1,col] := 'Low 95%';
|
||||
OS3MainFrm.DataGrid.Cells[col,0] := 'Low 95%';
|
||||
|
||||
col := NoVariables + 1;
|
||||
DictionaryFrm.NewVar(col);
|
||||
DictionaryFrm.DictGrid.Cells[1,col] := 'Top 95%';
|
||||
OS3MainFrm.DataGrid.Cells[col,0] := 'Top 95%';
|
||||
|
||||
for i := 1 to NoCases do
|
||||
begin
|
||||
{ get term1 of the std. err. prediction }
|
||||
@ -2348,5 +2361,50 @@ begin
|
||||
rv1 := nil;
|
||||
end;
|
||||
|
||||
{ Adds a new variable named AColTitle after the last grid column
|
||||
and writes the specified data to it in the specified number format.
|
||||
Rows mentioned in ABadRows must be omitted because they are not contained in
|
||||
AData. }
|
||||
procedure AddVariable(AVarName: String; AData: DblDyneVec;
|
||||
ANumFormat: String; const ABadRows: IntDyneVec);
|
||||
|
||||
function IsBadRow(ARow: Integer): Boolean;
|
||||
var
|
||||
j: Integer;
|
||||
begin
|
||||
for j := 0 to High(ABadRows) do
|
||||
if ARow = ABadRows[j] then
|
||||
begin
|
||||
Result := true;
|
||||
exit;
|
||||
end;
|
||||
Result := false;
|
||||
end;
|
||||
|
||||
var
|
||||
i, j, colIndex, row: Integer;
|
||||
begin
|
||||
colIndex := GetVariableIndex(OS3MainFrm.DataGrid, AVarname);
|
||||
if colIndex = -1 then
|
||||
begin
|
||||
colIndex := NoVariables + 1;
|
||||
DictionaryFrm.NewVar(colIndex);
|
||||
DictionaryFrm.DictGrid.Cells[1, colIndex] := AVarName;
|
||||
DictionaryFrm.DictGrid.Cells[7, colIndex] := 'R';
|
||||
OS3MainFrm.DataGrid.Cells[colIndex, 0] := AVarName;
|
||||
OS3MainFrm.NoVarsEdit.Text := IntToStr(NoVariables);
|
||||
end;
|
||||
row := 1;
|
||||
for i := 0 to High(AData) do
|
||||
begin
|
||||
while IsBadRow(row) do inc(row);
|
||||
if row >= OS3MainFrm.DataGrid.RowCount then
|
||||
raise Exception.Create('Bad row error.');
|
||||
OS3MainFrm.DataGrid.Cells[colIndex, row] := Format(ANumFormat, [AData[i]]);
|
||||
inc(row);
|
||||
end;
|
||||
end;
|
||||
|
||||
|
||||
end.
|
||||
|
||||
|
||||
@ -76,6 +76,8 @@ function MatRowVector(A: TDblMatrix; ARowIndex: Integer): TDblVector;
|
||||
procedure MatSize(A: TDblMatrix; out n, m: Integer);
|
||||
function MatTransposed(A: TDblMatrix): TDblMatrix;
|
||||
|
||||
function SubMatrix(A: TDblMatrix; i1,j1, i2,j2: Integer): TDblMatrix;
|
||||
|
||||
// Sorting
|
||||
procedure Exchange(var a, b: Double); overload;
|
||||
procedure Exchange(var a, b: Integer); overload;
|
||||
@ -685,6 +687,25 @@ begin
|
||||
end;
|
||||
|
||||
|
||||
function SubMatrix(A: TDblMatrix; i1,j1, i2,j2: Integer): TDblMatrix;
|
||||
var
|
||||
i, j, n, m: Integer;
|
||||
begin
|
||||
MatSize(A, n,m);
|
||||
i1 := EnsureRange(i1, 0, n);
|
||||
i2 := EnsureRange(i2, 0, n);
|
||||
j1 := EnsureRange(j1, 0, m);
|
||||
j2 := EnsureRange(j2, 0, m);
|
||||
if i1 > i2 then Exchange(i1, i2);
|
||||
if j1 > j2 then Exchange(j1, j2);
|
||||
|
||||
SetLength(Result, i2-i1+1, j2-j1+1);
|
||||
for i := i1 to i2 do
|
||||
for j := j1 to j2 do
|
||||
Result[i-i1, j-j1] := A[i, j];
|
||||
end;
|
||||
|
||||
|
||||
{===============================================================================
|
||||
TLUSolver
|
||||
--------------------------------------------------------------------------------
|
||||
|
||||
@ -43,8 +43,10 @@ type
|
||||
CoeffStdErrors: TDblVector; // Standard errors of the coefficients
|
||||
|
||||
Beta: TDblVector; // Standardized coefficients
|
||||
XT_X: TDblMatrix; // Cross-products matrix
|
||||
VarCovar: TDblMatrix; // Variance-covariance matrix
|
||||
Correlations: TDblMatrix; // Correlations matrix
|
||||
InvIndepCorrs: TDblMatrix; // Inverse of the INDEPENDENT correlation matrix
|
||||
|
||||
SStotal, SSreg, SSresid: Double; // Sum of squares
|
||||
NumCases, NumDepVars: Integer; // number of cases, number of dependent variables
|
||||
@ -59,24 +61,29 @@ type
|
||||
Means: TDblVector;
|
||||
Variances: TDblVector;
|
||||
StdDevs: TDblVector;
|
||||
(*
|
||||
|
||||
XMeans: TDblVector; // Means of the x columns
|
||||
XVariances: TDblVector; // Variances of the x columns
|
||||
XStdDevs: TDblVector; // Std Deviations of the x columns
|
||||
*)
|
||||
MeanY: Double; // Mean of y column
|
||||
VarianceY: Double; // Variance of y column
|
||||
StdDevY: Double; // Std Deviation of y column
|
||||
|
||||
YMean: Double; // Mean of y column
|
||||
YVariance: Double; // Variance of y column
|
||||
YStdDev: Double; // Std Deviation of y column
|
||||
|
||||
procedure WriteANOVAReport(AReport: TStrings);
|
||||
procedure WriteCoeffsReport(AReport: TStrings; AVarNames: TStringArray);
|
||||
procedure WriteCorrelationReport(AReport: TStrings; AVarNames: TStringArray);
|
||||
procedure WriteCrossProductsReport(AReport: TStrings; AVarNames: TStringArray);
|
||||
procedure WriteVarCovarReport(AReport: TStrings; AVarNames: TStringArray);
|
||||
end;
|
||||
|
||||
function MultipleRegression(const xData: TDblMatrix; const yData: TDblVector;
|
||||
AConfLevel: Double; out AResults: TMultipleRegressionResults): TRegressionError;
|
||||
|
||||
procedure PredictMR(const xData: TDblMatrix; const yData: TDblVector;
|
||||
const ARegressionResults: TMultipleRegressionResults;
|
||||
out zPred, zResid, RawPred, RawResid, StdErrPred, Hi95, Lo95: TDblVector);
|
||||
|
||||
|
||||
implementation
|
||||
|
||||
@ -171,6 +178,7 @@ begin
|
||||
|
||||
// Product of transposed augmented with augmented matrix
|
||||
XT_X := XT * X;
|
||||
AResults.XT_X := Matcopy(XT_X);
|
||||
|
||||
// Product of inverse of XT_X with XT_Y yields the coefficients. Intercept is last.
|
||||
inv_XT_X := MatInverse(XT_X);
|
||||
@ -187,23 +195,19 @@ begin
|
||||
AResults.Means[i] := XT_X[i, mx] / nx;
|
||||
AResults.Variances[i] := (XT_X[i, i] - sqr(AResults.Means[i]) * nx) / (nx - 1);
|
||||
AResults.StdDevs[i] := sqrt(AResults.Variances[i]);
|
||||
{
|
||||
if AResults.StdDevs[i] = 0.0 then
|
||||
begin
|
||||
Result := regStdDevZero;
|
||||
exit;
|
||||
end;
|
||||
}
|
||||
end;
|
||||
|
||||
// Variance-covariance matrix
|
||||
SetLength(AResults.VarCovar, mx, mx);
|
||||
SetLength(AResults.Correlations, mx, mx);
|
||||
with AResults do
|
||||
begin
|
||||
SetLength(VarCovar, mx, mx);
|
||||
SetLength(Correlations, mx, mx);
|
||||
for i := 0 to mx-1 do
|
||||
for j := 0 to mx-1 do
|
||||
begin
|
||||
AResults.VarCovar[i, j] := (XT_X[i, j] - XT_X[i, mx] * XT_X[j, mx] / nx) / (nx - 1);
|
||||
AResults.Correlations[i, j] := AResults.VarCovar[i, j] / (AResults.StdDevs[i] * AResults.StdDevs[j]);
|
||||
VarCovar[i, j] := (XT_X[i, j] - XT_X[i, mx] * XT_X[j, mx] / nx) / (nx - 1);
|
||||
Correlations[i, j] := VarCovar[i, j] / (StdDevs[i] * StdDevs[j]);
|
||||
end;
|
||||
end;
|
||||
|
||||
with AResults do
|
||||
@ -213,24 +217,17 @@ begin
|
||||
DFresid := NumCases - NumDepVars - 1;
|
||||
|
||||
// Calculate column means of xData
|
||||
// MatColMeanVarStdDev(X, XMeans, XVariances, XStdDevs);
|
||||
MatColMeanVarStdDev(xData, xMeans, xVariances, xStdDevs);
|
||||
|
||||
// Basic stats of y data column
|
||||
VecSumSS(yData, SY, SSY);
|
||||
MeanY := SY / NumCases;
|
||||
SStotal := SSY - sqr(MeanY) * NumCases; // needed for ANOVA
|
||||
VarianceY := SStotal / (NumCases - 1);
|
||||
StdDevY := sqrt(VarianceY);
|
||||
{
|
||||
if StdDevY = 0 then
|
||||
begin
|
||||
Result := regStdDevZero;
|
||||
exit;
|
||||
end;
|
||||
}
|
||||
yMean := SY / NumCases;
|
||||
SStotal := SSY - sqr(yMean) * NumCases; // needed for ANOVA
|
||||
yVariance := SStotal / (NumCases - 1);
|
||||
yStdDev := sqrt(yVariance);
|
||||
|
||||
// Standardized coefficients
|
||||
Beta := VecMultiply(Coeffs, StdDevs) * (1.0/StdDevY);
|
||||
Beta := VecMultiply(Coeffs, StdDevs) * (1.0/yStdDev);
|
||||
|
||||
// Get standard errors, squared multiple correlation, tests of significance
|
||||
SetLength(CoeffStdErrors, mx+1);
|
||||
@ -251,6 +248,8 @@ begin
|
||||
t[i] := Coeffs[i] / CoeffStdErrors[i];
|
||||
p[i] := ProbT(t[i], DFresid);
|
||||
end;
|
||||
|
||||
InvIndepCorrs := MatInverse(SubMatrix(Correlations, 0, 0, mx-1, mx-1));
|
||||
end;
|
||||
|
||||
Result := regOK;
|
||||
@ -266,13 +265,13 @@ begin
|
||||
DFtotal := NumCases - 1;
|
||||
DFresid := DFtotal - DFreg;
|
||||
AReport.Add('ANOVA');
|
||||
AReport.Add('------------------------------------------------------------------------------');
|
||||
AReport.Add('--------------------------------------------------------------------------');
|
||||
AReport.Add('SOURCE DF Sum of Squares Mean Square F Probability');
|
||||
AReport.Add('---------- --- ---------------- ---------------- ------------ -----------');
|
||||
AReport.Add('Regression %3d %16.3f %16.3f %12.4f %10.4f', [DFreg, SSreg, SSreg/DFreg, F, Probability]);
|
||||
AReport.Add('Residual %3d %16.3f %16.3f', [DFresid, SSresid, SSresid/DFresid]);
|
||||
AReport.Add('Total %3d %16.3f', [DFtotal, SStotal]);
|
||||
AReport.Add('------------------------------------------------------------------------------');
|
||||
AReport.Add('---------- --- ---------------- ---------------- -------- -----------');
|
||||
AReport.Add('Regression %4d %16.3f %16.3f %8.3f %10.3f', [DFreg, SSreg, SSreg/DFreg, F, Probability]);
|
||||
AReport.Add('Residual %4d %16.3f %16.3f', [DFresid, SSresid, SSresid/DFresid]);
|
||||
AReport.Add('Total %4d %16.3f', [DFtotal, SStotal]);
|
||||
AReport.Add('--------------------------------------------------------------------------');
|
||||
AReport.Add('');
|
||||
AReport.Add('R2: %10.4f', [R2]);
|
||||
AReport.Add('Adjusted R2: %10.4f', [AdjR2]);
|
||||
@ -291,9 +290,9 @@ var
|
||||
i, first, last: Integer;
|
||||
begin
|
||||
AReport.Add('COEFFICIENTS');
|
||||
AReport.Add('------------------------------------------------------------------------------');
|
||||
AReport.Add('--------------------------------------------------------------------------');
|
||||
AReport.Add(' Variable Unstandardized Std.Error Standardized t p ');
|
||||
AReport.Add('------------ -------------- ------------ ------------ --------- ---------');
|
||||
AReport.Add('------------ -------------- ------------ ------------ ------- -------');
|
||||
|
||||
first := 0;
|
||||
last := High(Coeffs);
|
||||
@ -307,10 +306,10 @@ begin
|
||||
else
|
||||
varName := Format('VAR.%d', [i+1]);
|
||||
|
||||
AReport.Add('%12s %14.3f %12.3f %12.3f %9.4f %9.4f',
|
||||
AReport.Add('%12s %14.3f %12.3f %12.3f %7.3f %7.3f',
|
||||
[varName, Coeffs[i], CoeffStdErrors[i], Beta[i], t[i], p[i]]);
|
||||
end;
|
||||
AReport.Add('------------------------------------------------------------------------------');
|
||||
AReport.Add('--------------------------------------------------------------------------');
|
||||
end;
|
||||
|
||||
|
||||
@ -323,12 +322,26 @@ begin
|
||||
end;
|
||||
|
||||
|
||||
{ Writes the cross-product matrix to a "report"
|
||||
The names of the independent variables are neede in the array AVarNames. }
|
||||
procedure TMultipleRegressionResults.WriteCrossProductsReport(AReport: TStrings;
|
||||
AVarNames: TStringArray);
|
||||
var
|
||||
saved: String;
|
||||
begin
|
||||
saved := AVarNames[High(AVarNames)];
|
||||
AVarNames[High(AVarNames)] := '(Intercept)';
|
||||
WriteMatrixReport(AReport, XT_X, 'CROSS-PRODUCT MATRIX', AVarNames);
|
||||
AVarNames[High(AVarNames)] := saved;
|
||||
end;
|
||||
|
||||
|
||||
procedure TMultipleRegressionResults.WriteMatrixReport(AReport: TStrings;
|
||||
AMatrix: TDblMatrix; ATitle: String; AVarNames: TStringArray);
|
||||
|
||||
function GetVarName(i: Integer): String;
|
||||
begin
|
||||
if i < High(AVarNames) then
|
||||
if i <= High(AVarNames) then
|
||||
Result := AVarNames[i]
|
||||
else
|
||||
Result := Format('VAR.%d', [i+1]);
|
||||
@ -376,5 +389,90 @@ begin
|
||||
end;
|
||||
|
||||
|
||||
procedure PredictMR(const xData: TDblMatrix; const yData: TDblVector;
|
||||
const ARegressionResults: TMultipleRegressionResults;
|
||||
out zPred, zResid, RawPred, RawResid, StdErrPred, Hi95, Lo95: TDblVector);
|
||||
var
|
||||
i, j, k, n, m: Integer;
|
||||
x, x1, x2, y: Double;
|
||||
term1, term2, t: Double;
|
||||
begin
|
||||
zPred := nil; // to silence the compiler
|
||||
zResid := nil;
|
||||
RawPred := nil;
|
||||
RawResid := nil;
|
||||
StdErrPred := nil;
|
||||
Hi95 := nil;
|
||||
Lo95 := nil;
|
||||
|
||||
MatSize(xData, n,m);
|
||||
|
||||
// z predicted and zResidual
|
||||
SetLength(zPred, n);
|
||||
SetLength(zResid, n);
|
||||
for i := 0 to n-1 do
|
||||
begin
|
||||
zPred[i] := 0;
|
||||
for j := 0 to m-1 do
|
||||
begin
|
||||
x := (xData[i, j] - ARegressionResults.xMeans[j]) / ARegressionResults.xStdDevs[j];
|
||||
zPred[i] := zPred[i] + ARegressionResults.Beta[j] * x;
|
||||
end;
|
||||
y := (yData[i] - ARegressionResults.yMean) / ARegressionResults.yStdDev;
|
||||
zResid[i] := y - zPred[i];
|
||||
end;
|
||||
|
||||
// Raw predicted and raw residuals
|
||||
SetLength(RawPred, n);
|
||||
SetLength(RawResid, n);
|
||||
for i := 0 to n-1 do
|
||||
begin
|
||||
RawPred[i] := ARegressionResults.Coeffs[m]; // intercept
|
||||
for j := 0 to m-1 do
|
||||
RawPred[i] := RawPred[i] + ARegressionResults.Coeffs[j] * xData[i, j];
|
||||
RawResid[i] := yData[i] - RawPred[i];
|
||||
end;
|
||||
|
||||
// Calculate confidence interval for raw predicted score
|
||||
SetLength(StdErrPred, n);
|
||||
SetLength(Hi95, n);
|
||||
SetLength(Lo95, n);
|
||||
|
||||
for i := 0 to n-1 do
|
||||
begin
|
||||
// Get term1 of the std. err. prediction
|
||||
term1 := 0.0;
|
||||
for j := 0 to m-1 do
|
||||
begin
|
||||
with ARegressionResults do
|
||||
begin
|
||||
x := (xData[i, j] - xMeans[j]) / xStdDevs[j];
|
||||
term1 := term1 + x * x * InvIndepCorrs[j, j];;
|
||||
end;
|
||||
end;
|
||||
|
||||
// Get term2 of the std err. of prediction
|
||||
term2 := 0.0;
|
||||
for j := 0 to m-1 do
|
||||
begin
|
||||
for k := j + 1 to m-1 do
|
||||
begin
|
||||
with ARegressionResults do
|
||||
begin
|
||||
x1 := (xData[i, j] - xMeans[j]) / xStdDevs[j];
|
||||
x2 := (xData[i, k] - xMeans[k]) / xStdDevs[k];
|
||||
term2 := term2 + x1 * x2 * InvIndepCorrs[j, k];
|
||||
end;
|
||||
end;
|
||||
end;
|
||||
term2 := 2.0 * Term2;
|
||||
stdErrPred[i] := sqrt(n + 1 + term1 + term2);
|
||||
stdErrPred[i] := (ARegressionResults.StdErrorEstimate / sqrt(n)) * stdErrPred[i];
|
||||
t := InverseT(0.975, n - m - 1);
|
||||
Lo95[i] := RawPred[i] - t*StdErrPred[i];
|
||||
Hi95[i] := RawPred[i] + t*StdErrPred[i];
|
||||
end;
|
||||
end;
|
||||
|
||||
end.
|
||||
|
||||
|
||||
Reference in New Issue
Block a user