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LazStats: Remove remaining code in GLMUnit writing a report directly to OutputFrm (instead of to a StringList).
git-svn-id: https://svn.code.sf.net/p/lazarus-ccr/svn@7453 8e941d3f-bd1b-0410-a28a-d453659cc2b4
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@ -303,8 +303,6 @@ end;
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procedure TANCOVAfrm.FormCreate(Sender: TObject);
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begin
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Assert(OS3MainFrm <> nil);
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if OutputFrm = nil then
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Application.CreateForm(TOutputFrm, OutputFrm);
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if GraphFrm = nil then
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Application.CreateForm(TGraphFrm, GraphFrm);
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end;
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@ -198,11 +198,11 @@ type
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procedure PartIEntry;
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procedure PartIIEntry;
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procedure ModelIAnalysis(AReport: TStrings);
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procedure ModelIIAnalysis;
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procedure ModelIIAnalysis(AReport: TStrings);
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procedure ModelIIIAnalysis(AReport: TStrings);
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function CntIntActVecs(linestr : string) : integer;
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procedure GenInterVecs(linestr : string);
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procedure CanCor(NLeft : integer; NRight : integer; GridPlace : IntDyneVec);
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procedure CanCor(NLeft : integer; NRight : integer; GridPlace : IntDyneVec; AReport: TStrings);
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procedure UpdateBtnStates;
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public
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@ -603,13 +603,13 @@ var
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begin
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if (NContDep = 0) and (NCatDep = 0) and (NReptDep = 0) then
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begin
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MessageDlg('No variables selected.', mtError, [mbOK], 0);
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ErrorMsg('No variables selected.');
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exit;
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end;
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if (NContDep > 0) and (NReptDep > 0) then
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begin
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MessageDlg('One cannot have both continuous and repeated dependent variables!', mtError, [mbOK], 0);
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ErrorMsg('One cannot have both continuous and repeated dependent variables!');
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exit;
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end;
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@ -619,6 +619,7 @@ begin
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GetIDs; // get var. no.s of dependent and independent variables
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novars := GetVarCount; // get total no. of variables to generate
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AllocateGridMem; // create data array for values and codes
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// Note, the Data Grid first subscript is row (subject) and second the var.
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if (NCatDep > 0) or (NContDep > 1) then
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model := 2
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@ -649,7 +650,7 @@ begin
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// Now, do the analyses
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case model of
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1: ModelIAnalysis(lReport); // models with 1 dependent variable
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2: ModelIIAnalysis; // models with 2 or more dependent var.s
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2: ModelIIAnalysis(lReport); // models with 2 or more dependent var.s
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3: ModelIIIAnalysis(lReport); // Repeated measures designs
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end;
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@ -1187,7 +1188,7 @@ begin
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DynCorrelations(nvars, ColSelected, DataGrid, rmatrix, means, vars, StdDevs, ncases, 3);
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AReport.Add('');
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AReport.Add('=======================================================================================');
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AReport.Add(DIVIDER);
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AReport.Add('');
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if DescChk.Checked then
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@ -1371,7 +1372,7 @@ begin
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DataGrid[i-1,gencount + vect - 1] := CodePattern[group,vect];
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end;
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ReptIndepPos[vect-1] := gencount + vect - 1;
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cellstring := format('p%d',[vect]);
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cellstring := Format('p%d', [vect]);
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GenLabels[gencount + vect - 1] := cellstring;
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end;
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gencount := gencount + (max - min); // new no. of variables
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@ -1701,7 +1702,7 @@ begin
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StdErrEst := sqrt(VarEst)
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else
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begin
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MessageDlg('Error in computing variance estimate.', mtError, [mbOK], 0);
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ErrorMsg('Error in computing variance estimate.');
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StdErrEst := 0.0;
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end;
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if (R2 < 1.0) and (df2 > 0.0) then
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@ -1765,7 +1766,7 @@ begin
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AReport.Add(' and Prob > F %10.3f', [FProbF]);
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AReport.Add('');
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AReport.Add('=======================================================================================');
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AReport.Add(DIVIDER);
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AReport.Add('');
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OldR2 := R2;
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@ -1851,7 +1852,7 @@ begin
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for k := 0 to NRndVecIndep[index]-1 do
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begin
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ColSelected[NEntered] := RndIndepPos[index] + k;
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Labels[NEntered] := Format('%s_%d',[RndIndepCode.Items[index], k+1]);
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Labels[NEntered] := Format('%s_%d', [RndIndepCode.Items[index], k+1]);
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NEntered := NEntered + 1;
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end;
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end;
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@ -1890,7 +1891,7 @@ begin
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StdErrEst := sqrt(VarEst)
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else
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begin
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MessageDlg('Error in computing variance estimate.', mtError, [mbOk], 0);
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ErrorMsg('Error in computing variance estimate.');
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StdErrEst := 0.0;
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end;
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if (R2 < 1.0) and (df2 > 0.0) then F := (R2 / df1) / ((1.0-R2)/ df2)
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@ -1945,7 +1946,7 @@ begin
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AReport.Add(' and Prob > F %10.3f', [FProbF]);
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AReport.Add('');
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AReport.Add('=======================================================================================');
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AReport.Add(DIVIDER);
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AReport.Add('');
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// setup for next block analysis
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@ -1987,7 +1988,7 @@ begin
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end;
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AReport.Add('');
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AReport.Add('=======================================================================================');
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AReport.Add(DIVIDER);
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AReport.Add('');
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// Show Anova Results for fixed and/or covariates
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@ -2016,7 +2017,7 @@ begin
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AReport.Add('%20s %4.0f %10.3f %10.3f', ['Residual', df2, SSres, VarEst]);
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AReport.Add('%20s %4d %10.3f', ['Total', totalobs-1, SSt]);
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AReport.Add('');
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AReport.Add('=======================================================================================');
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AReport.Add(DIVIDER);
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AReport.Add('');
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end;
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end;
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@ -2046,7 +2047,7 @@ begin
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AReport.Add('%20s %4.0f %10.3f %10.3f', ['Residual', df2, SSres, VarEst]);
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AReport.Add('%20s %4d %10.3f', ['Total', totalobs-1, SSt]);
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AReport.Add('');
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AReport.Add('=======================================================================================');
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AReport.Add(DIVIDER);
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AReport.Add('');
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end;
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end;
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@ -2074,7 +2075,7 @@ begin
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AReport.Add('%20s %4.0f %10.3f %10.3f', ['Residual', df2, SSres, VarEst]);
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AReport.Add('%20s %4d %10.3f', ['Total', totalobs-1, SSt]);
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AReport.Add('');
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AReport.Add('=======================================================================================');
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AReport.Add(DIVIDER);
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AReport.Add('');
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end;
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@ -2093,13 +2094,12 @@ begin
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TypeISS := nil;
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end;
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procedure TGLMFrm.ModelIIAnalysis;
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procedure TGLMFrm.ModelIIAnalysis(AReport: TStrings);
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var
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block, i, j, NEntered, index, noblocks : integer;
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NLeft, NRight : integer;
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cellstring : string;
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labelstr : string;
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begin
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NEntered := 0;
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OldR2 := 0;
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@ -2252,7 +2252,7 @@ begin
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NRight := NEntered - NLeft;
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// call cancor routine for this block
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cancor(NLeft,NRight,ColSelected);
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CanCor(NLeft, NRight, ColSelected, AReport);
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end; // next block
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TypeIIProb := nil;
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@ -2348,7 +2348,7 @@ begin
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for j := 0 to NFixVecIndep[index]-1 do
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begin
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ColSelected[NEntered] := FixedIndepPos[index] + j;
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labelstr := format('%s_%d',[FixedIndepCode.Items.Strings[index],j+1]);
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labelstr := Format('%s_%d', [FixedIndepCode.Items[index], j+1]);
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Labels[NEntered] := labelstr;
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NEntered := NEntered + 1;
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end;
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@ -2368,7 +2368,7 @@ begin
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for j := 0 to NRndVecIndep[index]-1 do
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begin
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ColSelected[NEntered] := RndIndepPos[index] + j;
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labelstr := format('%s_%d',[RndIndepCode.Items.Strings[index],j+1]);
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labelstr := Format('%s_%d', [RndIndepCode.Items[index], j+1]);
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Labels[NEntered] := labelstr;
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NEntered := NEntered + 1;
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end;
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@ -2390,7 +2390,7 @@ begin
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for j := 0 to NInteractVecs[i]-1 do
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begin
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ColSelected[NEntered] := InteractPos[i] + j;
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labelstr := format('%s%d_%d',['IA',i+1,j+1]);
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labelstr := Format('%s%d_%d', ['IA',i+1,j+1]);
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Labels[NEntered] := labelstr;
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NEntered := NEntered + 1;
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end;
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@ -2408,7 +2408,7 @@ begin
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begin
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index := i; // index of covariate code
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ColSelected[NEntered] := CovIndepPos[index];
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labelstr := format('%s',[CovariateCode.Items.Strings[index]]);
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labelstr := Format('%s', [CovariateCode.Items[index]]);
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Labels[NEntered] := labelstr;
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NEntered := NEntered + 1;
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break;
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@ -2430,7 +2430,7 @@ begin
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StdErrEst := sqrt(VarEst)
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else
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begin
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ShowMessage('ERROR! Error in computing variance estimate.');
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ErrorMsg('Error in computing variance estimate.');
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StdErrEst := 0.0;
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end;
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@ -2479,7 +2479,7 @@ begin
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AReport.Add('SS for %-10s: %10.3f',[effstr,TypeISS[block]]);
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AReport.Add('SS TOTAL: %10.3f',[SST]);
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AReport.Add('');
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AReport.Add('=======================================================================================');
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AReport.Add(DIVIDER);
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AReport.Add('');
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end;
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@ -2522,7 +2522,7 @@ begin
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end;
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AReport.Add('%20s %4.0f %10.3f %10.3f', ['Error Between', dferrbetween, sserrbetween, mserrbetween]);
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AReport.Add('');
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AReport.Add('=======================================================================================');
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AReport.Add(DIVIDER);
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AReport.Add('');
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// Now, get within subject effects
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@ -2635,7 +2635,7 @@ begin
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AReport.Add('SS for %-10s: %10.3f',[effstr, TypeIISS[block]]);
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AReport.Add('SS TOTAL: %10.3f',[SST]);
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AReport.Add('');
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AReport.Add('=======================================================================================');
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AReport.Add(DIVIDER);
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AReport.Add('');
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end;
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@ -2670,7 +2670,7 @@ begin
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AReport.Add('%20s %4d %10.3f', ['TOTAL', totalobs-1, SST]);
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AReport.Add('');
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AReport.Add('=======================================================================================');
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AReport.Add(DIVIDER);
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AReport.Add('');
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// clean up the heap
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@ -2954,7 +2954,7 @@ begin
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datagrid[m,col] := datagrid[m,pos1] *
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datagrid[m,pos2] * datagrid[m,pos3] *
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datagrid[m,pos4] * datagrid[m,pos5];
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cellstring := format('%s*%s*%s*%s*%s',[GenLabels[pos1],
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cellstring := Format('%s*%s*%s*%s*%s',[GenLabels[pos1],
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GenLabels[pos2],GenLabels[pos3],GenLabels[pos4],
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GenLabels[pos5]]);
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GenLabels[col] := cellstring;
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@ -2967,11 +2967,10 @@ begin
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end; // if listcnt = 3
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end;
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procedure TGLMFrm.CanCor(NLeft: integer; NRight: integer; GridPlace: IntDyneVec);
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label cleanup;
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procedure TGLMFrm.CanCor(NLeft: integer; NRight: integer; GridPlace: IntDyneVec;
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AReport: TStrings);
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var
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i, j, k, count, a_size, b_size, no_factors, IER: integer;
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outline: string;
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s, m, n, df1, df2, q, w, pcnt_extracted, trace : double;
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minroot, critical_prob, Lambda, Pillia : double;
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chisqr, HLTrace, chiprob, ftestprob, Roys, f, Hroot : double;
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@ -3067,16 +3066,16 @@ begin
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selected[NLeft+i] := GridPlace[NLeft+i];
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end;
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OutputFrm.RichEdit.Clear;
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OutputFrm.RichEdit.Lines.Add('CANONICAL CORRELATION ANALYSIS');
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OutputFrm.RichEdit.Lines.Add('');
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AReport.Add('CANONICAL CORRELATION ANALYSIS');
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AReport.Add('');
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count := NoCases;
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// Get means, standard deviations, etc. for total matrix
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IER := Dyncorrelations(novars,selected,datagrid,bigmat,mean,variance,stddev,totalobs,3);
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if (IER = 1)then
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IER := DynCorrelations(novars,selected,datagrid,bigmat,mean,variance,stddev,totalobs,3);
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if (IER = 1) then
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begin
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ShowMessage('ERROR! Zero variance found for a variable-terminating');
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goto cleanup;
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ErrorMsg('Zero variance found for a variable-terminating');
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exit;
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end;
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//partition matrix into quadrants
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@ -3098,13 +3097,15 @@ begin
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if CorsChk.Checked then
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begin
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title := 'Left Correlation Matrix';
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MAT_PRINT(raa,NLeft,NLeft,title,a_vars,a_vars,totalobs);
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MatPrint(raa, NLeft, NLeft, title, a_vars, a_vars, totalobs, AReport);
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title := 'Right Correlation Matrix';
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MAT_PRINT(rbb,NRight,NRight,title,b_vars,b_vars,totalobs);
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MatPrint(rbb, NRight, NRight, title, b_vars, b_vars, totalobs, AReport);
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title := 'Left-Right Correlation Matrix';
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MAT_PRINT(rab,NLeft,NRight,title,a_vars,b_vars,totalobs);
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OutputFrm.ShowModal;
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OutputFrm.RichEdit.Clear;
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MatPrint(rab, NLeft, NRight, title, a_vars, b_vars, totalobs, AReport);
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AReport.Add('');
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AReport.Add(DIVIDER);
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AReport.Add('');
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end;
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// get inverses of left and right hand matrices raa and rbb
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@ -3117,7 +3118,7 @@ begin
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if CorsChk.Checked then
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begin
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title := 'Inverse of Left Matrix';
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MAT_PRINT(raainv,a_size,a_size,title,a_vars,a_vars,totalobs);
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MatPrint(raainv, a_size, a_size, title, a_vars, a_vars, totalobs, AReport);
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end;
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for i := 0 to b_size-1 do
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@ -3129,7 +3130,7 @@ begin
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if CorsChk.Checked then
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begin
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title := 'Inverse of Right Matrix';
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MAT_PRINT(rbbinv,b_size,b_size,title,b_vars,b_vars,totalobs);
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MatPrint(rbbinv, b_size, b_size, title, b_vars, b_vars, totalobs, AReport);
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end;
|
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// get products of raainv x rab and the rbbinv x rba matrix
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@ -3140,9 +3141,9 @@ begin
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for j := 0 to b_size-1 do second_prod[i,j] := 0.0;
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MatAxB(second_prod,raainv,rab,a_size,a_size,a_size,b_size,errorcode);
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title := 'Right Inverse x Right-Left Matrix';
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MAT_PRINT(first_prod,b_size,a_size,title,b_vars,a_vars,totalobs);
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MatPrint(first_prod, b_size, a_size, title, b_vars, a_vars, totalobs, AReport);
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title := 'Left Inverse x Left-Right Matrix';
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MAT_PRINT(second_prod,a_size,b_size,title,a_vars,b_vars,totalobs);
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MatPrint(second_prod, a_size, b_size, title, a_vars, b_vars, totalobs, AReport);
|
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|
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//get characteristic equations matrix (product of last two product matrices
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//The product should yeild rows and cols representing the smaller of the two sets
|
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@ -3150,9 +3151,11 @@ begin
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for j := 0 to b_size - 1 do char_equation[i,j] := 0.0;
|
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MatAxB(char_equation,first_prod,second_prod,b_size,a_size,a_size,b_size,errorcode);
|
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title := 'Canonical Function';
|
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MAT_PRINT(char_equation,b_size,b_size,title,CanLabels,CanLabels,totalobs);
|
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OutputFrm.ShowModal;
|
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OutputFrm.RichEdit.Clear;
|
||||
MatPrint(char_equation, b_size, b_size, title, CanLabels, CanLabels, totalobs, AReport);
|
||||
|
||||
AReport.Add('');
|
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AReport.Add(DIVIDER);
|
||||
AReport.Add('');
|
||||
|
||||
// now get roots and vectors of the characteristic equation using
|
||||
// NonSymRoots routine
|
||||
@ -3169,10 +3172,8 @@ begin
|
||||
pcnt_trace, trace, pcnt_extracted);
|
||||
|
||||
|
||||
outline := format('Trace of the matrix:=%10.4f',[trace]);
|
||||
OutputFrm.RichEdit.Lines.Add(outline);
|
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outline := format('Percent of trace extracted: %10.4f',[pcnt_extracted]);
|
||||
OutputFrm.RichEdit.Lines.Add(outline);
|
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AReport.Add('Trace of the matrix: %10.4f', [trace]);
|
||||
AReport.Add('Percent of trace extracted: %10.4f', [pcnt_extracted]);
|
||||
|
||||
// Normalize smaller set weights and coumpute larger set weights
|
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for i := 0 to b_size - 1 do // transpose eigenvectors
|
||||
@ -3266,24 +3267,20 @@ begin
|
||||
end;
|
||||
|
||||
// Print remaining results
|
||||
OutputFrm.RichEdit.Lines.Add('');
|
||||
OutputFrm.RichEdit.Lines.Add('');
|
||||
outline := ' Canonical R Root % Trace Chi-Sqr D.F. Prob.';
|
||||
OutputFrm.RichEdit.Lines.Add(outline);
|
||||
AReport.Add('');
|
||||
AReport.Add('');
|
||||
AReport.Add(' Canonical R Root % Trace Chi-Sqr D.F. Prob.');
|
||||
for i := 0 to b_size-1 do
|
||||
begin
|
||||
outline := format('%2d %10.6f %8.3f %7.3f %8.3f %2d %8.3f',
|
||||
[i+1, sqrt(roots[i]), roots[i], pcnt_trace[i], root_chi[i], root_df[i], chi_prob[i]]);
|
||||
OutputFrm.RichEdit.Lines.Add(outline);
|
||||
end;
|
||||
AReport.Add('%2d %10.6f %8.3f %7.3f %8.3f %2d %8.3f',
|
||||
[i+1, sqrt(roots[i]), roots[i], pcnt_trace[i], root_chi[i], root_df[i], chi_prob[i]]);
|
||||
|
||||
chisqr := -ln(Lambda) * (count - 1.0 - 0.5 * (a_size + b_size - 1.0));
|
||||
chiprob := 1.0 - chisquaredprob(chisqr,a_size * b_size);
|
||||
OutputFrm.RichEdit.Lines.Add('');
|
||||
OutputFrm.RichEdit.Lines.Add('Overall Tests of Significance:');
|
||||
OutputFrm.RichEdit.Lines.Add(' Statistic Approx. Stat. Value D.F. Prob.>Value');
|
||||
outline := format('Wilk''s Lambda Chi-Squared %10.4f %3d %6.4f',
|
||||
[chisqr,a_size * b_size,chiprob]);
|
||||
OutputFrm.RichEdit.Lines.Add(outline);
|
||||
AReport.Add('');
|
||||
AReport.Add('Overall Tests of Significance:');
|
||||
AReport.Add(' Statistic Approx. Stat. Value D.F. Prob.>Value');
|
||||
AReport.Add('Wilk''s Lambda Chi-Squared %10.4f %3d %6.4f', [chisqr,a_size * b_size,chiprob]);
|
||||
|
||||
s := b_size;
|
||||
m := 0.5 * (a_size - b_size - 1);
|
||||
n := 0.5 * (count - b_size - a_size - 2);
|
||||
@ -3291,78 +3288,80 @@ begin
|
||||
df1 := s * (2.0 * m + s + 1.0);
|
||||
df2 := 2.0 * ( s * n + 1.0);
|
||||
ftestprob := probf(f,df1,df2);
|
||||
outline := format('Hotelling-Lawley Trace F-Test %10.4f %2.0f %2.0f %6.4f',
|
||||
[f, df1,df2, ftestprob]);
|
||||
OutputFrm.RichEdit.Lines.Add(outline);
|
||||
AReport.Add('Hotelling-Lawley Trace F-Test %10.4f %2.0f %2.0f %6.4f', [f, df1, df2, ftestprob]);
|
||||
|
||||
df2 := s * (2.0 * n + s + 1.0);
|
||||
f := (Pillia / (s - Pillia)) * ( (2.0 * n + s +1.0) / (2.0 * m + s + 1.0) );
|
||||
ftestprob := probf(f,df1,df2);
|
||||
outline := format('Pillai Trace F-Test %10.4f %2.0f %2.0f %6.4f',
|
||||
[f, df1,df2, ftestprob]);
|
||||
OutputFrm.RichEdit.Lines.Add(outline);
|
||||
AReport.Add('Pillai Trace F-Test %10.4f %2.0f %2.0f %6.4f', [f, df1, df2, ftestprob]);
|
||||
|
||||
Roys := Roys * (count - 1 - a_size + b_size)/ a_size ;
|
||||
df1 := a_size;
|
||||
df2 := count - 1 - a_size + b_size;
|
||||
ftestprob := probf(Roys,df1,df2);
|
||||
outline := format('Roys Largest Root F-Test %10.4f %2.0f %2.0f %6.4f',
|
||||
[Roys, df1, df2, ftestprob]);
|
||||
OutputFrm.RichEdit.Lines.Add(outline);
|
||||
OutputFrm.ShowModal;
|
||||
OutputFrm.RichEdit.Clear;
|
||||
AReport.Add('Roys Largest Root F-Test %10.4f %2.0f %2.0f %6.4f', [Roys, df1, df2, ftestprob]);
|
||||
|
||||
AReport.Add('');
|
||||
AReport.Add(DIVIDER);
|
||||
AReport.Add('');
|
||||
|
||||
if CorsChk.Checked then
|
||||
begin
|
||||
title := 'Eigenvectors';
|
||||
MAT_PRINT(eigenvectors,b_size,b_size,title,CanLabels,CanLabels,totalobs);
|
||||
OutputFrm.ShowModal();
|
||||
OutputFrm.RichEdit.Clear;
|
||||
MatPrint(eigenvectors, b_size, b_size, title, CanLabels, CanLabels, totalobs, AReport);
|
||||
AReport.Add('');
|
||||
AReport.Add(DIVIDER);
|
||||
AReport.Add('');
|
||||
end;
|
||||
|
||||
title := 'Standardized Right Side Weights';
|
||||
MAT_PRINT(norm_a,a_size,b_size,title,RowLabels,CanLabels,totalobs);
|
||||
MatPrint(norm_a, a_size, b_size, title, RowLabels, CanLabels, totalobs, AReport);
|
||||
|
||||
title := 'Standardized Left Side Weights';
|
||||
MAT_PRINT(norm_b,b_size,b_size,title,ColLabels,CanLabels,totalobs);
|
||||
OutputFrm.ShowModal;
|
||||
MatPrint(norm_b, b_size, b_size, title, ColLabels, CanLabels, totalobs, AReport);
|
||||
|
||||
AReport.Add('');
|
||||
AReport.Add(DIVIDER);
|
||||
AReport.Add('');
|
||||
|
||||
title := 'Raw Right Side Weights';
|
||||
MAT_PRINT(raw_a,a_size,b_size,title,RowLabels,CanLabels,totalobs);
|
||||
MatPrint(raw_a, a_size, b_size, title, RowLabels, CanLabels, totalobs, AReport);
|
||||
|
||||
title := 'Raw Left Side Weights';
|
||||
MAT_PRINT(raw_b,b_size,b_size,title,ColLabels,CanLabels,totalobs);
|
||||
OutputFrm.ShowModal;
|
||||
MatPrint(raw_b, b_size, b_size, title, ColLabels, CanLabels, totalobs, AReport);
|
||||
|
||||
AReport.Add('');
|
||||
AReport.Add(DIVIDER);
|
||||
AReport.Add('');
|
||||
|
||||
title := 'Right Side Correlations with Function';
|
||||
MAT_PRINT(a_cors,a_size,b_size,title,RowLabels,CanLabels,totalobs);
|
||||
MatPrint(a_cors, a_size, b_size, title, RowLabels, CanLabels, totalobs, AReport);
|
||||
title := 'Left Side Correlations with Function';
|
||||
MAT_PRINT(b_cors,b_size,b_size,title,ColLabels,CanLabels,totalobs);
|
||||
OutputFrm.ShowModal;
|
||||
OutputFrm.RichEdit.Clear;
|
||||
MatPrint(b_cors, b_size, b_size, title, ColLabels, CanLabels, totalobs, AReport);
|
||||
|
||||
AReport.Add('');
|
||||
AReport.Add(DIVIDER);
|
||||
AReport.Add('');
|
||||
|
||||
if CorsChk.Checked then
|
||||
begin
|
||||
outline := 'Redundancy Analysis for Right Side Variables';
|
||||
OutputFrm.RichEdit.Lines.Add(outline);
|
||||
OutputFrm.RichEdit.Lines.Add('');
|
||||
outline := ' Variance Prop. Redundancy';
|
||||
OutputFrm.RichEdit.Lines.Add(outline);
|
||||
AReport.Add('Redundancy Analysis for Right Side Variables');
|
||||
AReport.Add('');
|
||||
AReport.Add(' Variance Prop. Redundancy');
|
||||
for i := 0 to b_size-1 do
|
||||
begin
|
||||
outline := format('%10d %10.5f %10.5f',[i,pv_a[i],rd_a[i]]);
|
||||
OutputFrm.RichEdit.Lines.Add(outline);
|
||||
end;
|
||||
OutputFrm.RichEdit.Lines.Add('');
|
||||
outline := 'Redundancy Analysis for Left Side Variables';
|
||||
OutputFrm.RichEdit.Lines.Add(outline);
|
||||
outline := ' Variance Prop. Redundancy';
|
||||
OutputFrm.RichEdit.Lines.Add(outline);
|
||||
AReport.Add('%10d %10.5f %10.5f', [i, pv_a[i], rd_a[i]]);
|
||||
AReport.Add('');
|
||||
AReport.Add('Redundancy Analysis for Left Side Variables');
|
||||
AReport.Add(' Variance Prop. Redundancy');
|
||||
for i := 0 to b_size-1 do
|
||||
begin
|
||||
outline := format('%10d %10.5f %10.5f',[i,pv_b[i],rd_b[i]]);
|
||||
OutputFrm.RichEdit.Lines.Add(outline);
|
||||
end;
|
||||
OutputFrm.ShowModal;
|
||||
OutputFrm.RichEdit.Clear;
|
||||
AReport.Add('%10d %10.5f %10.5f', [i, pv_b[i], rd_b[i]]);
|
||||
|
||||
AReport.Add('');
|
||||
AReport.Add(DIVIDER);
|
||||
AReport.Add('');
|
||||
end;
|
||||
|
||||
//------------- Now, clean up memory mess ----------------------------
|
||||
cleanup:
|
||||
selected := nil;
|
||||
ColLabels := nil;
|
||||
RowLabels := nil;
|
||||
|
||||
Reference in New Issue
Block a user