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LazStats: Refactor CurSimUnit. Add its pdf to chm help. Some cleanup.
git-svn-id: https://svn.code.sf.net/p/lazarus-ccr/svn@7441 8e941d3f-bd1b-0410-a28a-d453659cc2b4
This commit is contained in:
wp_xxyyzz
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@ -125,7 +125,6 @@ var
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cumfreq : DblDyneVec;
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prank : DblDyneVec;
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grpsize : IntDyneVec;
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scrgrp : DblDyneVec;
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done : boolean;
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NoSelected : integer;
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ColNoSelected : IntDyneVec;
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@ -173,7 +172,7 @@ begin
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NoGrps := maxgrp - mingrp + 1;
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if NoGrps > 30 then
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begin
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MessageDlg('Too many groups for meaningful plot.', mtError, [mbOK], 0);
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MessageDlg('Too many groups for a meaningful plot.', mtError, [mbOK], 0);
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exit;
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end;
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@ -189,7 +188,6 @@ begin
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SetLength(tenpcntile,NoGrps+1);
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SetLength(ninetypcntile,NoGrps+1);
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SetLength(median,NoGrps+1);
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SetLength(scrgrp,NoGrps+1);
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// initialize
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for j := 1 to NoGrps do
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@ -325,7 +323,6 @@ begin
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lReport.Free;
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// Clean up
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scrgrp := nil;
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median := nil;
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ninetypcntile := nil;
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tenpcntile := nil;
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@ -81,7 +81,7 @@ var
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i, j, btn, nscores: integer;
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RawScores: array[0..50] of double;
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RawFreq: array[0..50] of double;
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temp, X, Y: double;
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X: double;
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begin
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if DistUseGroup.ItemIndex < 0 then
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exit;
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@ -105,12 +105,8 @@ begin
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for i := 1 to ncases - 1 do
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begin
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for j := i+1 to ncases do
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begin
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X := RawScores[i-1];
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Y := RawScores[j-1];
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if RawScores[i-1] < RawScores[j-1] then // switch
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Exchange(RawScores[i-1], RawScores[j-1]);
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end;
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end;
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// get frequency of each score
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@ -1589,8 +1589,8 @@ end;
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// Call HTML help (.chm file)
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// Is is expected that help topics are specified as HelpKeyword (HelpType = htContext).
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// Using numeric HelpContext values will crash the application.
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function TOS3MainFrm.HelpHandler(Command:word; Data:PtrInt;
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var CallHelp:Boolean): Boolean;
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function TOS3MainFrm.HelpHandler(Command: Word; Data: PtrInt;
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var CallHelp: Boolean): Boolean;
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var
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topic: UnicodeString;
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begin
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@ -1599,6 +1599,9 @@ begin
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// Don't call regular help
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CallHelp := False;
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// silence the compiler, function result not needed
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Result := true;
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end;
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{$ENDIF}
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{$ENDIF}
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@ -3,10 +3,11 @@ object CorSimFrm: TCorSimFrm
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Height = 447
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Top = 126
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Width = 857
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HelpType = htKeyword
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HelpKeyword = 'BivariateScatterPlot.htm'
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Caption = 'Correlation Simulation'
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ClientHeight = 447
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ClientWidth = 857
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OnCreate = FormCreate
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OnShow = FormShow
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Position = poMainFormCenter
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LCLVersion = '2.1.0.0'
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@ -114,6 +115,7 @@ object CorSimFrm: TCorSimFrm
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Height = 23
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Top = 2
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Width = 43
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Alignment = taRightJustify
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BorderSpacing.Left = 6
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OnKeyPress = MeanXKeyPress
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TabOrder = 0
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@ -127,6 +129,7 @@ object CorSimFrm: TCorSimFrm
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Height = 23
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Top = 2
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Width = 46
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Alignment = taRightJustify
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BorderSpacing.Left = 8
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OnKeyPress = MeanYKeyPress
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TabOrder = 1
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@ -140,6 +143,7 @@ object CorSimFrm: TCorSimFrm
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Height = 23
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Top = 2
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Width = 50
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Alignment = taRightJustify
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BorderSpacing.Left = 8
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OnKeyPress = SDXKeyPress
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TabOrder = 2
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@ -153,6 +157,7 @@ object CorSimFrm: TCorSimFrm
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Height = 23
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Top = 2
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Width = 39
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Alignment = taRightJustify
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BorderSpacing.Left = 8
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OnKeyPress = SDYKeyPress
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TabOrder = 3
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@ -166,14 +171,15 @@ object CorSimFrm: TCorSimFrm
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Height = 23
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Top = 2
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Width = 44
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Alignment = taRightJustify
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BorderSpacing.Left = 8
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OnKeyPress = CorrKeyPress
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TabOrder = 4
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Text = 'Corr'
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end
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object ComputeBtn: TButton
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AnchorSideTop.Control = ReturnBtn
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AnchorSideRight.Control = ReturnBtn
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AnchorSideTop.Control = CloseBtn
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AnchorSideRight.Control = CloseBtn
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Left = 702
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Height = 26
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Top = 0
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@ -182,9 +188,9 @@ object CorSimFrm: TCorSimFrm
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BorderSpacing.Right = 8
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Caption = 'Compute'
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OnClick = ComputeBtnClick
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TabOrder = 5
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TabOrder = 6
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end
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object ReturnBtn: TButton
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object CloseBtn: TButton
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AnchorSideTop.Control = Panel1
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AnchorSideTop.Side = asrCenter
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AnchorSideRight.Control = Panel1
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@ -194,9 +200,9 @@ object CorSimFrm: TCorSimFrm
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Top = 0
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Width = 66
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Anchors = [akTop, akRight]
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Caption = 'Return'
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ModalResult = 1
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TabOrder = 6
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Caption = 'Close'
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ModalResult = 11
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TabOrder = 7
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end
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object Nobs: TEdit
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AnchorSideLeft.Control = Label6
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@ -206,9 +212,10 @@ object CorSimFrm: TCorSimFrm
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Height = 23
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Top = 2
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Width = 40
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Alignment = taRightJustify
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BorderSpacing.Left = 8
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OnKeyPress = NobsKeyPress
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TabOrder = 7
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TabOrder = 5
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Text = 'Nobs'
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end
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end
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@ -18,7 +18,7 @@ type
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Nobs: TEdit;
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Image1: TImage;
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Label6: TLabel;
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ReturnBtn: TButton;
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CloseBtn: TButton;
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ComputeBtn: TButton;
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Corr: TEdit;
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Label5: TLabel;
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@ -33,7 +33,6 @@ type
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Panel1: TPanel;
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procedure ComputeBtnClick(Sender: TObject);
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procedure CorrKeyPress(Sender: TObject; var Key: char);
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procedure FormCreate(Sender: TObject);
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procedure FormShow(Sender: TObject);
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procedure MeanXKeyPress(Sender: TObject; var Key: char);
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procedure MeanYKeyPress(Sender: TObject; var Key: char);
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@ -45,10 +44,11 @@ type
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xmean, ymean, xsd, ysd, corxy, corsqr, yvariance, predvar : double;
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errvariance, stderror, b, constant, newxmean, newymean : double;
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newxsd, newysd, newcorr, randomerror, newb, newconstant : double;
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x, y : DblDyneVec;
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freqx, freqy : IntDyneVec;
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N : integer;
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procedure plot(Sender: TObject);
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x, y: DblDyneVec;
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freqx, freqy: IntDyneVec;
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N: integer;
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procedure Plot;
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function Validate(out AMsg: String; out AControl: TWinControl): Boolean;
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public
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{ public declarations }
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end;
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@ -62,314 +62,401 @@ implementation
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procedure TCorSimFrm.MeanXKeyPress(Sender: TObject; var Key: char);
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begin
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if Ord(Key) = 13 then MeanY.SetFocus;
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if Key = #13 then MeanY.SetFocus;
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end;
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procedure TCorSimFrm.CorrKeyPress(Sender: TObject; var Key: char);
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begin
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if Ord(Key) = 13 then Nobs.SetFocus;
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end;
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procedure TCorSimFrm.FormCreate(Sender: TObject);
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begin
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if OutputFrm = nil then
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Application.CreateForm(TOutputFrm, OutputFrm);
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if Key = #13 then Nobs.SetFocus;
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end;
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procedure TCorSimFrm.ComputeBtnClick(Sender: TObject);
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var
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outline : string;
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i : integer;
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i: integer;
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msg: String;
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C: TWinControl;
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lReport: TStrings;
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begin
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N := StrToInt(NObs.Text);
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xmean := StrToFloat(MeanX.Text);
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ymean := StrToFloat(MeanY.Text);
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xsd := StrToFloat(SDX.Text);
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ysd := StrToFloat(SDY.Text);
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corxy := StrToFloat(Corr.Text);
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Randomize;
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if not Validate(msg, C) then begin
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C.SetFocus;
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MessageDlg(msg, mtError, [mbOk], 0);
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exit;
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end;
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SetLength(freqx,N + 1);
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SetLength(freqy,N + 1);
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SetLength(x,N + 1);
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SetLength(y,N + 1);
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N := StrToInt(NObs.Text);
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xmean := StrToFloat(MeanX.Text);
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ymean := StrToFloat(MeanY.Text);
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xsd := StrToFloat(SDX.Text);
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ysd := StrToFloat(SDY.Text);
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corxy := StrToFloat(Corr.Text);
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// generate x and y data observations
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corsqr := corxy * corxy;
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yvariance := ysd * ysd;
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predvar := corsqr * yvariance;
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errvariance := yvariance - predvar;
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stderror := sqrt(errvariance);
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b := corxy * (ysd / xsd);
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constant := ymean - (b * xmean);
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Randomize;
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newxmean := 0.0;
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newymean := 0.0;
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newxsd := 0.0;
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newysd := 0.0;
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newcorr := 0.0;
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SetLength(freqx, N + 1);
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SetLength(freqy, N + 1);
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SetLength(x, N + 1);
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SetLength(y, N + 1);
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// generate x and y data observations
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corsqr := corxy * corxy;
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yvariance := ysd * ysd;
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predvar := corsqr * yvariance;
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errvariance := yvariance - predvar;
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stderror := sqrt(errvariance);
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b := corxy * (ysd / xsd);
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constant := ymean - b * xmean;
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newxmean := 0.0;
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newymean := 0.0;
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newxsd := 0.0;
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newysd := 0.0;
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newcorr := 0.0;
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for i := 1 to N do
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begin
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x[i] := RandG(xmean, xsd);
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randomerror := RandG(0.0, stderror);
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y[i] := b * x[i] + constant + randomerror;
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newxmean := newxmean + x[i];
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newymean := newymean + y[i];
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newxsd := newxsd + sqr(x[i]);
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newysd := newysd + sqr(y[i]);
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newcorr := newcorr + x[i] * y[i];
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end;
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newxsd := newxsd - sqr(newxmean) / N;
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newxsd := newxsd / (N - 1);
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newxsd := sqrt(newxsd);
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newysd := newysd - sqr(newymean) / N;
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newysd := newysd / (N - 1);
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newysd := sqrt(newysd);
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newcorr := newcorr - newxmean * newymean / N;
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newcorr := newcorr / (N - 1);
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newcorr := newcorr / (newxsd * newysd);
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newxmean := newxmean / N;
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newymean := newymean / N;
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newb := newcorr * (newysd / newxsd);
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newconstant := newymean - newb * newxmean;
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lReport := TStringList.Create;
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try
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lReport.Add('POPULATION PARAMETERS FOR THE SIMULATION');
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lReport.Add('');
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lReport.Add('Mean X: %8.3f', [xmean]);
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lReport.Add('Std. Dev. X: %8.3f', [xsd]);
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lReport.Add('');
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lReport.Add('Mean Y: %8.3f', [ymean]);
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lReport.Add('Std. Dev. Y: %8.3f', [ysd]);
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lReport.Add('');
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lReport.Add('Product-Moment Correlation: %8.3f', [corxy]);
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lReport.Add('Regression line slope: %8.3f', [b]);
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lReport.Add(' constant: %8.3f', [constant]);
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lReport.Add('');
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lReport.Add(DIVIDER);
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lReport.Add('');
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lReport.Add('SAMPLE STATISTICS FOR %d OBSERVATIONS FROM THE POPULATION', [N]);
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lReport.Add('');
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lReport.Add('Mean X: %8.3f', [newxmean]);
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lReport.Add('Std. Dev. X: %8.3f', [newxsd]);
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lReport.Add('');
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lReport.Add('Mean Y: %8.3f', [newymean]);
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lReport.Add('Std. Dev. Y: %8.3f', [newysd]);
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lReport.Add('');
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lReport.Add('Product-Moment Correlation: %8.3f', [newcorr]);
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lReport.Add('Regression line slope: %8.3f', [newb]);
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lReport.Add(' constant: %8.3f', [newconstant]);
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lReport.Add('');
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lReport.Add(DIVIDER);
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lReport.Add('');
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lReport.Add('Pair No. X Y ');
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lReport.Add('-------- --------- ---------');
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for i := 1 to N do
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begin
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x[i] := RandG(xmean,xsd);
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randomerror := RandG(0.0,stderror);
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y[i] := (b * x[i]) + constant + randomerror;
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newxmean := newxmean + x[i];
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newymean := newymean + y[i];
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newxsd := newxsd + (x[i] * x[i]);
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newysd := newysd + (y[i] * y[i]);
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newcorr := newcorr + (x[i] * y[i]);
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end;
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newxsd := newxsd - ((newxmean * newxmean) / N);
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newxsd := newxsd / (N - 1.0);
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newxsd := sqrt(newxsd);
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newysd := newysd - ((newymean * newymean) / N);
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newysd := newysd / (N - 1.0);
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newysd := sqrt(newysd);
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newcorr := newcorr - ((newxmean * newymean) / N);
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newcorr := newcorr / (N - 1.0);
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newcorr := newcorr / (newxsd * newysd);
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newxmean := newxmean / N;
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newymean := newymean / N;
|
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newb := newcorr * (newysd / newxsd);
|
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newconstant := newymean - (newb * newxmean);
|
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OutputFrm.RichEdit.Lines.Clear;
|
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outline := 'POPULATION PARAMETERS FOR THE SIMULATION';
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OutputFrm.RichEdit.Lines.Add(outline);
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OutputFrm.RichEdit.Lines.Add('');
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outline := format('Mean X := %8.3f, Std. Dev. X := %8.3f',[xmean, xsd]);
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OutputFrm.RichEdit.Lines.Add(outline);
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outline := format('Mean Y := %8.3f, Std. Dev. Y := %8.3f',[ymean, ysd]);
|
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OutputFrm.RichEdit.Lines.Add(outline);
|
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outline := format('Product-Moment Correlation := %8.3f',[corxy]);
|
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OutputFrm.RichEdit.Lines.Add(outline);
|
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outline := format('Regression line slope := %8.3f, constant := %8.3f',
|
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[b, constant]);
|
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OutputFrm.RichEdit.Lines.Add(outline);
|
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OutputFrm.RichEdit.Lines.Add('');
|
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OutputFrm.RichEdit.Lines.Add('');
|
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outline := format('SAMPLE STATISTICS FOR %d OBSERVATIONS FROM THE POPULATION',[N]);
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OutputFrm.RichEdit.Lines.Add(outline);
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OutputFrm.RichEdit.Lines.Add('');
|
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outline := format('Mean X := %8.3f, Std. Dev. X := %8.3f',[newxmean, newxsd]);
|
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OutputFrm.RichEdit.Lines.Add(outline);
|
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outline := format('Mean Y := %8.3f, Std. Dev. Y := %8.3f',[newymean, newysd]);
|
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OutputFrm.RichEdit.Lines.Add(outline);
|
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outline := format('Product-Moment Correlation := %8.3f',[newcorr]);
|
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OutputFrm.RichEdit.Lines.Add(outline);
|
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outline := format('Regression line slope := %8.3f, constant := %8.3f',
|
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[newb, newconstant]);
|
||||
OutputFrm.RichEdit.Lines.Add(outline);
|
||||
OutputFrm.RichEdit.Lines.Add('');
|
||||
OutputFrm.RichEdit.Lines.Add('Pair No. X Y');
|
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for i := 1 to N do
|
||||
begin
|
||||
outline := format(' %3d %9.3f %9.3f',[i,x[i],y[i]]);
|
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OutputFrm.RichEdit.Lines.Add(outline);
|
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end;
|
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OutputFrm.ShowModal;
|
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plot(self);
|
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lReport.Add(' %4d %8.3f %8.3f', [i, x[i], y[i]]);
|
||||
|
||||
DisplayReport(lReport);
|
||||
|
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Plot();
|
||||
|
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finally
|
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lReport.Free;
|
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freqx := nil;
|
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freqy := nil;
|
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x := nil;
|
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y := nil;
|
||||
ReturnBtn.SetFocus;
|
||||
end;
|
||||
end;
|
||||
|
||||
procedure TCorSimFrm.FormShow(Sender: TObject);
|
||||
begin
|
||||
Image1.Canvas.Pen.Color := clBlack;
|
||||
Image1.Canvas.Brush.Color := clWhite;
|
||||
Image1.Canvas.Rectangle(0, 0, Image1.Width, Image1.Height);
|
||||
//Image1.Canvas.FloodFill(1,1,clWhite,fsborder);
|
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MeanX.Text := '100';
|
||||
MeanY.Text := '100';
|
||||
SDX.Text := '15';
|
||||
SDY.Text := '15';
|
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Corr.Text := '.8';
|
||||
Nobs.Text := '100';
|
||||
Image1.Canvas.Pen.Color := clBlack;
|
||||
Image1.Canvas.Brush.Color := clWhite;
|
||||
Image1.Canvas.Rectangle(0, 0, Image1.Width, Image1.Height);
|
||||
|
||||
MeanX.Text := '100';
|
||||
MeanY.Text := '100';
|
||||
SDX.Text := '15';
|
||||
SDY.Text := '15';
|
||||
Corr.Text := '.8';
|
||||
Nobs.Text := '100';
|
||||
end;
|
||||
|
||||
procedure TCorSimFrm.MeanYKeyPress(Sender: TObject; var Key: char);
|
||||
begin
|
||||
if Ord(Key) = 13 then SDX.SetFocus;
|
||||
if Key = #13 then SDX.SetFocus;
|
||||
end;
|
||||
|
||||
procedure TCorSimFrm.NobsKeyPress(Sender: TObject; var Key: char);
|
||||
begin
|
||||
if Ord(Key) = 13 then ComputeBtn.SetFocus;
|
||||
if Key = #13 then ComputeBtn.SetFocus;
|
||||
end;
|
||||
|
||||
procedure TCorSimFrm.SDXKeyPress(Sender: TObject; var Key: char);
|
||||
begin
|
||||
if Ord(Key) = 13 then SDY.SetFocus;
|
||||
if Key = #13 then SDY.SetFocus;
|
||||
end;
|
||||
|
||||
procedure TCorSimFrm.SDYKeyPress(Sender: TObject; var Key: char);
|
||||
begin
|
||||
if Ord(Key) = 13 then Corr.SetFocus;
|
||||
if Key = #13 then Corr.SetFocus;
|
||||
end;
|
||||
|
||||
procedure TCorSimFrm.plot(Sender: TObject);
|
||||
procedure TCorSimFrm.Plot;
|
||||
var
|
||||
minx, maxx, miny, maxy, xincrement, yincrement : double;
|
||||
predy1, predy2, lowerx, upperx, frange, prop : double;
|
||||
charlabel : string;
|
||||
xpos, ypos, xpos1, ypos1, xpos2, ypos2 : integer;
|
||||
i, winwidth, winheight, xoffset, yoffset, xaxislong, yaxislong : integer;
|
||||
j, xspacing, yspacing, labelwidth, minfreq, maxfreq : integer;
|
||||
flength, theight, lowery, uppery : integer;
|
||||
minx, maxx, miny, maxy, xincrement, yincrement: double;
|
||||
predy1, predy2, lowerx, upperx, frange, prop: double;
|
||||
charlabel: string;
|
||||
xpos, ypos, xpos1, ypos1, xpos2, ypos2: integer;
|
||||
i, winwidth, winheight, xoffset, yoffset, xaxislong, yaxislong: integer;
|
||||
j, xspacing, yspacing, labelwidth, minfreq, maxfreq: integer;
|
||||
flength, theight, lowery, uppery: integer;
|
||||
begin
|
||||
// get min and max of x and y points
|
||||
minx := x[1];
|
||||
maxx := minx;
|
||||
miny := y[1];
|
||||
maxy := miny;
|
||||
for i := 1 to N do
|
||||
begin
|
||||
if (minx > x[i]) then minx := x[i];
|
||||
if (maxx < x[i]) then maxx := x[i];
|
||||
if (miny > y[i]) then miny := y[i];
|
||||
if (maxy < y[i]) then maxy := y[i];
|
||||
end;
|
||||
xincrement := (maxx - minx) / 10;
|
||||
yincrement := (maxy - miny) / 10;
|
||||
// get min and max of x and y points
|
||||
minx := x[1];
|
||||
maxx := minx;
|
||||
miny := y[1];
|
||||
maxy := miny;
|
||||
for i := 1 to N do
|
||||
begin
|
||||
if (minx > x[i]) then minx := x[i];
|
||||
if (maxx < x[i]) then maxx := x[i];
|
||||
if (miny > y[i]) then miny := y[i];
|
||||
if (maxy < y[i]) then maxy := y[i];
|
||||
end;
|
||||
xincrement := (maxx - minx) / 10;
|
||||
yincrement := (maxy - miny) / 10;
|
||||
|
||||
winwidth := Image1.Width;
|
||||
winheight := Image1.Height;
|
||||
xoffset := winwidth div 5;
|
||||
yoffset := winheight div 5;
|
||||
xaxislong := winwidth - xoffset- winwidth div 10;
|
||||
yaxislong := winheight - yoffset - winheight div 10;
|
||||
Image1.Canvas.Pen.Color := clBlack;
|
||||
Image1.Canvas.MoveTo(xoffset,yaxislong);
|
||||
Image1.Canvas.LineTo(winwidth,yaxislong);
|
||||
Image1.Canvas.MoveTo(xoffset,yaxislong);
|
||||
Image1.Canvas.LineTo(xoffset,0);
|
||||
xspacing := xaxislong div 10;
|
||||
yspacing := yaxislong div 10;
|
||||
// do xaxis
|
||||
for i := 0 to 11 do
|
||||
begin
|
||||
Image1.Canvas.MoveTo(xoffset + (i * xspacing),yaxislong);
|
||||
Image1.Canvas.LineTo(xoffset + (i * xspacing),yaxislong + 10);
|
||||
charlabel := format('%8.3f',[minx + (i * xincrement)]);
|
||||
labelwidth := Image1.Canvas.TextWidth(charlabel);
|
||||
xpos := xoffset + (i * xspacing)-labelwidth div 2;
|
||||
ypos := yaxislong + 12;
|
||||
Image1.Canvas.TextOut(xpos,ypos,charlabel);
|
||||
end;
|
||||
// do yaxis
|
||||
for i := 0 to 11 do
|
||||
begin
|
||||
Image1.Canvas.MoveTo(xoffset, yaxislong - (i * yspacing));
|
||||
Image1.Canvas.LineTo(xoffset-10,yaxislong - (i * yspacing));
|
||||
charlabel := format('%8.3f',[miny + (i * yincrement)]);
|
||||
labelwidth := Image1.Canvas.TextWidth(charlabel);
|
||||
xpos := xoffset-10-labelwidth;
|
||||
ypos := yaxislong - (i * yspacing);
|
||||
Image1.Canvas.TextOut(xpos,ypos,charlabel);
|
||||
end;
|
||||
// plot points
|
||||
Image1.Canvas.Pen.Color := clRed;
|
||||
for i := 1 to N do
|
||||
begin
|
||||
xpos := round(xoffset + ((x[i] - minx) / (maxx - minx) * xaxislong));
|
||||
ypos := round(yaxislong - ((y[i] - miny) / (maxy - miny) * yaxislong));
|
||||
Image1.Canvas.Ellipse(xpos,ypos,xpos+5,ypos+5);
|
||||
end;
|
||||
// draw regression line
|
||||
Image1.Canvas.Pen.Color := clBlack;
|
||||
predy1 := newb * minx + newconstant;
|
||||
predy2 := newb * maxx + newconstant;
|
||||
xpos1 := xoffset;
|
||||
xpos2 := xoffset + xaxislong;
|
||||
ypos1 := round(yaxislong - ((predy1 - miny) / (maxy - miny) * yaxislong));
|
||||
ypos2 := round(yaxislong - ((predy2 - miny) / (maxy - miny) * yaxislong));
|
||||
Image1.Canvas.MoveTo(xpos1,ypos1);
|
||||
Image1.Canvas.LineTo(xpos2,ypos2);
|
||||
winwidth := Image1.Width;
|
||||
winheight := Image1.Height;
|
||||
xoffset := winwidth div 5;
|
||||
yoffset := winheight div 5;
|
||||
xaxislong := winwidth - xoffset- winwidth div 10;
|
||||
yaxislong := winheight - yoffset - winheight div 10;
|
||||
xspacing := xaxislong div 10;
|
||||
yspacing := yaxislong div 10;
|
||||
|
||||
// do x frequency distribution
|
||||
xincrement := (maxx-minx) / 50.0;
|
||||
xspacing := xaxislong div 50;
|
||||
for j := 1 to 51 do freqx[j] := 0;
|
||||
for i := 1 to N do
|
||||
begin
|
||||
for j := 1 to 51 do
|
||||
begin
|
||||
lowerx := minx + (j * xincrement);
|
||||
upperx := minx + ((j+1) * xincrement);
|
||||
if ((x[i] >= lowerx) and (x[i] < upperx)) then freqx[j] := freqx[j] + 1;
|
||||
end;
|
||||
end;
|
||||
// plot the x frequencies
|
||||
minfreq := N;
|
||||
maxfreq := 0;
|
||||
for j := 1 to 51 do
|
||||
begin
|
||||
if (freqx[j] > maxfreq) then maxfreq := freqx[j];
|
||||
if (freqx[j] < minfreq) then minfreq := freqx[j];
|
||||
end;
|
||||
flength := winheight - (yaxislong + 25) - Panel1.Height;
|
||||
for j := 1 to 51 do
|
||||
begin
|
||||
xpos := xoffset + (j * xspacing);
|
||||
ypos1 := round(yaxislong + 25 +
|
||||
((freqx[j] - minfreq)/ (maxfreq-minfreq) * (flength)));
|
||||
ypos2 := yaxislong + 25;
|
||||
Image1.Canvas.MoveTo(xpos,ypos1);
|
||||
Image1.Canvas.LineTo(xpos,ypos2);
|
||||
end;
|
||||
Image1.Canvas.MoveTo(xoffset,yaxislong+25);
|
||||
Image1.Canvas.LineTo(winwidth,yaxislong+25);
|
||||
xpos := 20;
|
||||
ypos := yaxislong+30;
|
||||
Image1.Canvas.TextOut(xpos,ypos,'X DISTRIBUTION');
|
||||
theight := Image1.Canvas.TextHeight('X');
|
||||
ypos := ypos + theight;
|
||||
charlabel := format('correlation := %6.3f',[newcorr]);
|
||||
Image1.Canvas.TextOut(xpos,ypos,charlabel);
|
||||
ypos := ypos + theight;
|
||||
charlabel := format('Mean X := %8.3f, Mean Y := %8.3f',[newxmean, newymean]);
|
||||
Image1.Canvas.TextOut(xpos,ypos,charlabel);
|
||||
charlabel := format('SD X := %8.3f, SD Y := %8.3f',[newxsd, newysd]);
|
||||
ypos := ypos + theight;
|
||||
Image1.Canvas.TextOut(xpos,ypos,charlabel);
|
||||
Image1.Canvas.Pen.Color := clBlack;
|
||||
Image1.Canvas.Line(xoffset, yaxislong, winwidth, yaxislong);
|
||||
Image1.canvas.Line(xoffset, yaxislong, xoffset, 0);
|
||||
|
||||
// do y frequency distribution
|
||||
yincrement := (maxy-miny) / 50.0;
|
||||
yspacing := yaxislong div 50;
|
||||
for j := 1 to 51 do freqy[j] := 0;
|
||||
for i := 1 to N do
|
||||
begin
|
||||
for j := 1 to 51 do
|
||||
begin
|
||||
lowery := round(miny + (j * yincrement));
|
||||
uppery := round(miny + ((j+1) * yincrement));
|
||||
if ((y[i] >= lowery) and (y[i] < uppery)) then freqy[j] := freqy[j] + 1;
|
||||
end;
|
||||
end;
|
||||
// plot the y frequencies
|
||||
minfreq := N;
|
||||
maxfreq := 0;
|
||||
// do xaxis
|
||||
for i := 0 to 11 do
|
||||
begin
|
||||
Image1.Canvas.Line(xoffset + i * xspacing, yaxislong, xoffset + i * xspacing, yaxislong + 10);
|
||||
charlabel := Format('%.3f', [minx + i * xincrement]);
|
||||
labelwidth := Image1.Canvas.TextWidth(charlabel);
|
||||
xpos := xoffset + i * xspacing - labelwidth div 2;
|
||||
ypos := yaxislong + 12;
|
||||
Image1.Canvas.TextOut(xpos, ypos, charlabel);
|
||||
end;
|
||||
|
||||
// do yaxis
|
||||
for i := 0 to 11 do
|
||||
begin
|
||||
Image1.Canvas.Line(xoffset, yaxislong - i * yspacing, xoffset-10, yaxislong - i * yspacing);
|
||||
charlabel := Format('%.3f', [miny + i * yincrement]);
|
||||
labelwidth := Image1.Canvas.TextWidth(charlabel);
|
||||
xpos := xoffset - 10 - labelwidth;
|
||||
ypos := yaxislong - i * yspacing;
|
||||
Image1.Canvas.TextOut(xpos, ypos, charlabel);
|
||||
end;
|
||||
|
||||
// plot points
|
||||
Image1.Canvas.Pen.Color := clRed;
|
||||
for i := 1 to N do
|
||||
begin
|
||||
xpos := round(xoffset + ((x[i] - minx) / (maxx - minx) * xaxislong));
|
||||
ypos := round(yaxislong - ((y[i] - miny) / (maxy - miny) * yaxislong));
|
||||
Image1.Canvas.Ellipse(xpos, ypos, xpos+5, ypos+5);
|
||||
end;
|
||||
|
||||
// draw regression line
|
||||
Image1.Canvas.Pen.Color := clBlack;
|
||||
predy1 := newb * minx + newconstant;
|
||||
predy2 := newb * maxx + newconstant;
|
||||
xpos1 := xoffset;
|
||||
xpos2 := xoffset + xaxislong;
|
||||
ypos1 := round(yaxislong - ((predy1 - miny) / (maxy - miny) * yaxislong));
|
||||
ypos2 := round(yaxislong - ((predy2 - miny) / (maxy - miny) * yaxislong));
|
||||
Image1.Canvas.Line(xpos1, ypos1, xpos2, ypos2);
|
||||
|
||||
// do x frequency distribution
|
||||
xincrement := (maxx - minx) / 50.0;
|
||||
xspacing := xaxislong div 50;
|
||||
for j := 1 to 51 do
|
||||
freqx[j] := 0;
|
||||
for i := 1 to N do
|
||||
begin
|
||||
for j := 1 to 51 do
|
||||
begin
|
||||
if (freqy[j] > maxfreq) then maxfreq := freqy[j];
|
||||
if (freqy[j] < minfreq) then minfreq := freqy[j];
|
||||
lowerx := minx + j * xincrement;
|
||||
upperx := minx + (j+1) * xincrement;
|
||||
if (x[i] >= lowerx) and (x[i] < upperx) then
|
||||
freqx[j] := freqx[j] + 1;
|
||||
end;
|
||||
flength := winwidth - (xaxislong + 150);
|
||||
end;
|
||||
|
||||
// plot the x frequencies
|
||||
minfreq := N;
|
||||
maxfreq := 0;
|
||||
for j := 1 to 51 do
|
||||
begin
|
||||
if (freqx[j] > maxfreq) then
|
||||
maxfreq := freqx[j];
|
||||
if (freqx[j] < minfreq) then
|
||||
minfreq := freqx[j];
|
||||
end;
|
||||
flength := winheight - (yaxislong + 25) - Panel1.Height;
|
||||
for j := 1 to 51 do
|
||||
begin
|
||||
xpos := xoffset + j * xspacing;
|
||||
ypos1 := round(yaxislong + 25 + (freqx[j] - minfreq)/ (maxfreq-minfreq) * flength);
|
||||
ypos2 := yaxislong + 25;
|
||||
Image1.Canvas.Line(xpos, ypos1, xpos, ypos2);
|
||||
end;
|
||||
Image1.Canvas.Line(xoffset, yaxislong+25, winwidth, yaxislong+25);
|
||||
|
||||
xpos := 20;
|
||||
ypos := yaxislong+30;
|
||||
Image1.Canvas.TextOut(xpos, ypos, 'X DISTRIBUTION');
|
||||
|
||||
theight := Image1.Canvas.TextHeight('X');
|
||||
ypos := ypos + theight;
|
||||
charlabel := Format('Correlation: %.3f', [newcorr]);
|
||||
Image1.Canvas.TextOut(xpos, ypos, charlabel);
|
||||
ypos := ypos + theight;
|
||||
charlabel := Format('Mean X: %.3f; Mean Y: %.3f', [newxmean, newymean]);
|
||||
Image1.Canvas.TextOut(xpos, ypos, charlabel);
|
||||
charlabel := Format('SD X: %.3f; SD Y: %.3f', [newxsd, newysd]);
|
||||
ypos := ypos + theight;
|
||||
Image1.Canvas.TextOut(xpos,ypos,charlabel);
|
||||
|
||||
// do y frequency distribution
|
||||
yincrement := (maxy-miny) / 50.0;
|
||||
yspacing := yaxislong div 50;
|
||||
for j := 1 to 51 do
|
||||
freqy[j] := 0;
|
||||
for i := 1 to N do
|
||||
begin
|
||||
for j := 1 to 51 do
|
||||
begin
|
||||
ypos := yaxislong - (j * yspacing);
|
||||
frange := maxfreq - minfreq;
|
||||
prop := (freqy[j] - minfreq) / frange;
|
||||
xpos1 := round(xoffset - 50 - (prop * flength));
|
||||
xpos2 := xoffset - 50;
|
||||
Image1.Canvas.MoveTo(xpos1,ypos);
|
||||
Image1.Canvas.LineTo(xpos2,ypos);
|
||||
lowery := round(miny + j * yincrement);
|
||||
uppery := round(miny + ((j+1) * yincrement));
|
||||
if (y[i] >= lowery) and (y[i] < uppery) then
|
||||
freqy[j] := freqy[j] + 1;
|
||||
end;
|
||||
Image1.Canvas.MoveTo(xoffset - 50,yaxislong);
|
||||
Image1.Canvas.LineTo(xoffset - 50,0);
|
||||
Image1.Canvas.TextOut(0,0,'Y DISTRIBUTION');
|
||||
end;
|
||||
|
||||
// plot the y frequencies
|
||||
minfreq := N;
|
||||
maxfreq := 0;
|
||||
for j := 1 to 51 do
|
||||
begin
|
||||
if (freqy[j] > maxfreq) then maxfreq := freqy[j];
|
||||
if (freqy[j] < minfreq) then minfreq := freqy[j];
|
||||
end;
|
||||
flength := winwidth - (xaxislong + 150);
|
||||
for j := 1 to 51 do
|
||||
begin
|
||||
ypos := yaxislong - j * yspacing;
|
||||
frange := maxfreq - minfreq;
|
||||
prop := (freqy[j] - minfreq) / frange;
|
||||
xpos1 := round(xoffset - 50 - prop * flength);
|
||||
xpos2 := xoffset - 50;
|
||||
Image1.Canvas.Line(xpos1, ypos, xpos2, ypos);
|
||||
end;
|
||||
Image1.Canvas.Line(xoffset - 50, yaxislong, xoffset - 50, 0);
|
||||
Image1.Canvas.TextOut(0,0,'Y DISTRIBUTION');
|
||||
end;
|
||||
|
||||
function TCorSimFrm.Validate(out AMsg: String; out AControl: TWinControl): Boolean;
|
||||
begin
|
||||
Result := false;
|
||||
|
||||
if (MeanX.Text = '') or (MeanY.Text = '') or
|
||||
(SDX.Text = '') or (SDY.Text = '') or
|
||||
(Corr.Text = '') or (NObs.Text = '') then
|
||||
begin
|
||||
if MeanX.Text = '' then
|
||||
AControl := MeanX
|
||||
else if MeanY.Text = '' then
|
||||
AControl := MeanY
|
||||
else if SDX.Text = '' then
|
||||
AControl := SDX
|
||||
else if SDY.Text = '' then
|
||||
AControl := SDY
|
||||
else if Corr.Text = '' then
|
||||
AControl := Corr
|
||||
else if NObs.Text = '' then
|
||||
AControl := NObs;
|
||||
AMsg := 'Input cannot be empty.';
|
||||
exit;
|
||||
end;
|
||||
|
||||
if not TryStrToFloat(MeanX.Text, xMean) then
|
||||
begin
|
||||
AControl := MeanX;
|
||||
AMsg := 'Mean X must be a valid number.';
|
||||
exit;
|
||||
end;
|
||||
|
||||
if not TryStrToFloat(MeanY.Text, yMean) then
|
||||
begin
|
||||
AControl := MeanY;
|
||||
AMsg := 'Mean Y must be a valid number.';
|
||||
exit;
|
||||
end;
|
||||
|
||||
if not TryStrToFloat(SDX.Text, xSD) or (xSD <= 0) then
|
||||
begin
|
||||
AControl := SDX;
|
||||
AMsg := 'Std.Dev X must be a valid positive number.';
|
||||
exit;
|
||||
end;
|
||||
|
||||
if not TryStrToFloat(SDY.Text, ySD) or (ySD <= 0) then
|
||||
begin
|
||||
AControl := SDY;
|
||||
AMsg := 'Std.Dev Y must be a valid positive number.';
|
||||
exit;
|
||||
end;
|
||||
|
||||
if not TryStrToFloat(Corr.Text, corXY) then
|
||||
begin
|
||||
AControl := Corr;
|
||||
AMsg := 'Correlation XY must be a valid number.';
|
||||
exit;
|
||||
end;
|
||||
|
||||
if not TryStrToInt(NObs.Text, N) or (N <= 0) then
|
||||
begin
|
||||
AControl := NObs;
|
||||
AMsg := 'Number of observations must be a valid positive integer.';
|
||||
exit;
|
||||
end;
|
||||
|
||||
Result := true;
|
||||
end;
|
||||
|
||||
initialization
|
||||
|
||||
@ -78,7 +78,7 @@ procedure MReg(NoIndep : integer;
|
||||
procedure MReg(NoIndep: integer; const IndepCols: IntDyneVec; DepCol: integer;
|
||||
const RowLabels: StrDyneVec;
|
||||
const Means, Variances, StdDevs, BWeights, BetaWeights, BStdErrs, Bttests, tProbs: DblDyneVec;
|
||||
out R2, StdErrEst: double; out NCases: integer; out ErrorCode: boolean;
|
||||
out R2, StdErrEst: double; NCases: integer; out ErrorCode: boolean;
|
||||
PrintAll: boolean; AReport: TStrings);
|
||||
|
||||
procedure Dynnonsymroots(var a : DblDyneMat; nv : integer;
|
||||
@ -699,7 +699,7 @@ end;
|
||||
procedure MReg(NoIndep: integer; const IndepCols: IntDyneVec; DepCol: integer;
|
||||
const RowLabels: StrDyneVec;
|
||||
const Means, Variances, StdDevs, BWeights, BetaWeights, BStdErrs, Bttests, tProbs: DblDyneVec;
|
||||
out R2, StdErrEst: double; out NCases: integer; out ErrorCode: boolean;
|
||||
out R2, StdErrEst: double; NCases: integer; out ErrorCode: boolean;
|
||||
PrintAll: boolean; AReport: TStrings);
|
||||
var
|
||||
i, j, N: integer;
|
||||
|
||||
Reference in New Issue
Block a user