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LazStats: Remove remaining code in GLMUnit writing a report directly to OutputFrm (instead of to a StringList).

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git-svn-id: https://svn.code.sf.net/p/lazarus-ccr/svn@7453 8e941d3f-bd1b-0410-a28a-d453659cc2b4
This commit is contained in:
wp_xxyyzz
2020-05-13 20:23:26 +00:00
parent 92a0c02e8f
commit 9eaa49b4c6
3 changed files with 114 additions and 117 deletions
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BIN
applications/lazstats/docs/HelpNDoc/LazStats.hnd
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2
applications/lazstats/source/forms/analysis/comparisons/ancovaunit.pas
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@@ -303,8 +303,6 @@ end;
procedure TANCOVAfrm.FormCreate(Sender: TObject); procedure TANCOVAfrm.FormCreate(Sender: TObject);
begin begin
Assert(OS3MainFrm <> nil); Assert(OS3MainFrm <> nil);
if OutputFrm = nil then
Application.CreateForm(TOutputFrm, OutputFrm);
if GraphFrm = nil then if GraphFrm = nil then
Application.CreateForm(TGraphFrm, GraphFrm); Application.CreateForm(TGraphFrm, GraphFrm);
end; end;

227
applications/lazstats/source/forms/analysis/comparisons/glmunit.pas
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@@ -198,11 +198,11 @@ type
procedure PartIEntry; procedure PartIEntry;
procedure PartIIEntry; procedure PartIIEntry;
procedure ModelIAnalysis(AReport: TStrings); procedure ModelIAnalysis(AReport: TStrings);
procedure ModelIIAnalysis; procedure ModelIIAnalysis(AReport: TStrings);
procedure ModelIIIAnalysis(AReport: TStrings); procedure ModelIIIAnalysis(AReport: TStrings);
function CntIntActVecs(linestr : string) : integer; function CntIntActVecs(linestr : string) : integer;
procedure GenInterVecs(linestr : string); procedure GenInterVecs(linestr : string);
procedure CanCor(NLeft : integer; NRight : integer; GridPlace : IntDyneVec); procedure CanCor(NLeft : integer; NRight : integer; GridPlace : IntDyneVec; AReport: TStrings);
procedure UpdateBtnStates; procedure UpdateBtnStates;
public public
@@ -603,13 +603,13 @@ var
begin begin
if (NContDep = 0) and (NCatDep = 0) and (NReptDep = 0) then if (NContDep = 0) and (NCatDep = 0) and (NReptDep = 0) then
begin begin
MessageDlg('No variables selected.', mtError, [mbOK], 0); ErrorMsg('No variables selected.');
exit; exit;
end; end;
if (NContDep > 0) and (NReptDep > 0) then if (NContDep > 0) and (NReptDep > 0) then
begin begin
MessageDlg('One cannot have both continuous and repeated dependent variables!', mtError, [mbOK], 0); ErrorMsg('One cannot have both continuous and repeated dependent variables!');
exit; exit;
end; end;
@@ -619,6 +619,7 @@ begin
GetIDs; // get var. no.s of dependent and independent variables GetIDs; // get var. no.s of dependent and independent variables
novars := GetVarCount; // get total no. of variables to generate novars := GetVarCount; // get total no. of variables to generate
AllocateGridMem; // create data array for values and codes AllocateGridMem; // create data array for values and codes
// Note, the Data Grid first subscript is row (subject) and second the var. // Note, the Data Grid first subscript is row (subject) and second the var.
if (NCatDep > 0) or (NContDep > 1) then if (NCatDep > 0) or (NContDep > 1) then
model := 2 model := 2
@@ -649,7 +650,7 @@ begin
// Now, do the analyses // Now, do the analyses
case model of case model of
1: ModelIAnalysis(lReport); // models with 1 dependent variable 1: ModelIAnalysis(lReport); // models with 1 dependent variable
2: ModelIIAnalysis; // models with 2 or more dependent var.s 2: ModelIIAnalysis(lReport); // models with 2 or more dependent var.s
3: ModelIIIAnalysis(lReport); // Repeated measures designs 3: ModelIIIAnalysis(lReport); // Repeated measures designs
end; end;
@@ -1187,7 +1188,7 @@ begin
DynCorrelations(nvars, ColSelected, DataGrid, rmatrix, means, vars, StdDevs, ncases, 3); DynCorrelations(nvars, ColSelected, DataGrid, rmatrix, means, vars, StdDevs, ncases, 3);
AReport.Add(''); AReport.Add('');
AReport.Add('======================================================================================='); AReport.Add(DIVIDER);
AReport.Add(''); AReport.Add('');
if DescChk.Checked then if DescChk.Checked then
@@ -1371,7 +1372,7 @@ begin
DataGrid[i-1,gencount + vect - 1] := CodePattern[group,vect]; DataGrid[i-1,gencount + vect - 1] := CodePattern[group,vect];
end; end;
ReptIndepPos[vect-1] := gencount + vect - 1; ReptIndepPos[vect-1] := gencount + vect - 1;
cellstring := format('p%d',[vect]); cellstring := Format('p%d', [vect]);
GenLabels[gencount + vect - 1] := cellstring; GenLabels[gencount + vect - 1] := cellstring;
end; end;
gencount := gencount + (max - min); // new no. of variables gencount := gencount + (max - min); // new no. of variables
@@ -1701,7 +1702,7 @@ begin
StdErrEst := sqrt(VarEst) StdErrEst := sqrt(VarEst)
else else
begin begin
MessageDlg('Error in computing variance estimate.', mtError, [mbOK], 0); ErrorMsg('Error in computing variance estimate.');
StdErrEst := 0.0; StdErrEst := 0.0;
end; end;
if (R2 < 1.0) and (df2 > 0.0) then if (R2 < 1.0) and (df2 > 0.0) then
@@ -1765,7 +1766,7 @@ begin
AReport.Add(' and Prob > F %10.3f', [FProbF]); AReport.Add(' and Prob > F %10.3f', [FProbF]);
AReport.Add(''); AReport.Add('');
AReport.Add('======================================================================================='); AReport.Add(DIVIDER);
AReport.Add(''); AReport.Add('');
OldR2 := R2; OldR2 := R2;
@@ -1851,7 +1852,7 @@ begin
for k := 0 to NRndVecIndep[index]-1 do for k := 0 to NRndVecIndep[index]-1 do
begin begin
ColSelected[NEntered] := RndIndepPos[index] + k; ColSelected[NEntered] := RndIndepPos[index] + k;
Labels[NEntered] := Format('%s_%d',[RndIndepCode.Items[index], k+1]); Labels[NEntered] := Format('%s_%d', [RndIndepCode.Items[index], k+1]);
NEntered := NEntered + 1; NEntered := NEntered + 1;
end; end;
end; end;
@@ -1890,7 +1891,7 @@ begin
StdErrEst := sqrt(VarEst) StdErrEst := sqrt(VarEst)
else else
begin begin
MessageDlg('Error in computing variance estimate.', mtError, [mbOk], 0); ErrorMsg('Error in computing variance estimate.');
StdErrEst := 0.0; StdErrEst := 0.0;
end; end;
if (R2 < 1.0) and (df2 > 0.0) then F := (R2 / df1) / ((1.0-R2)/ df2) if (R2 < 1.0) and (df2 > 0.0) then F := (R2 / df1) / ((1.0-R2)/ df2)
@@ -1945,7 +1946,7 @@ begin
AReport.Add(' and Prob > F %10.3f', [FProbF]); AReport.Add(' and Prob > F %10.3f', [FProbF]);
AReport.Add(''); AReport.Add('');
AReport.Add('======================================================================================='); AReport.Add(DIVIDER);
AReport.Add(''); AReport.Add('');
// setup for next block analysis // setup for next block analysis
@@ -1987,7 +1988,7 @@ begin
end; end;
AReport.Add(''); AReport.Add('');
AReport.Add('======================================================================================='); AReport.Add(DIVIDER);
AReport.Add(''); AReport.Add('');
// Show Anova Results for fixed and/or covariates // Show Anova Results for fixed and/or covariates
@@ -2016,7 +2017,7 @@ begin
AReport.Add('%20s %4.0f %10.3f %10.3f', ['Residual', df2, SSres, VarEst]); AReport.Add('%20s %4.0f %10.3f %10.3f', ['Residual', df2, SSres, VarEst]);
AReport.Add('%20s %4d %10.3f', ['Total', totalobs-1, SSt]); AReport.Add('%20s %4d %10.3f', ['Total', totalobs-1, SSt]);
AReport.Add(''); AReport.Add('');
AReport.Add('======================================================================================='); AReport.Add(DIVIDER);
AReport.Add(''); AReport.Add('');
end; end;
end; end;
@@ -2046,7 +2047,7 @@ begin
AReport.Add('%20s %4.0f %10.3f %10.3f', ['Residual', df2, SSres, VarEst]); AReport.Add('%20s %4.0f %10.3f %10.3f', ['Residual', df2, SSres, VarEst]);
AReport.Add('%20s %4d %10.3f', ['Total', totalobs-1, SSt]); AReport.Add('%20s %4d %10.3f', ['Total', totalobs-1, SSt]);
AReport.Add(''); AReport.Add('');
AReport.Add('======================================================================================='); AReport.Add(DIVIDER);
AReport.Add(''); AReport.Add('');
end; end;
end; end;
@@ -2074,7 +2075,7 @@ begin
AReport.Add('%20s %4.0f %10.3f %10.3f', ['Residual', df2, SSres, VarEst]); AReport.Add('%20s %4.0f %10.3f %10.3f', ['Residual', df2, SSres, VarEst]);
AReport.Add('%20s %4d %10.3f', ['Total', totalobs-1, SSt]); AReport.Add('%20s %4d %10.3f', ['Total', totalobs-1, SSt]);
AReport.Add(''); AReport.Add('');
AReport.Add('======================================================================================='); AReport.Add(DIVIDER);
AReport.Add(''); AReport.Add('');
end; end;
@@ -2093,13 +2094,12 @@ begin
TypeISS := nil; TypeISS := nil;
end; end;
procedure TGLMFrm.ModelIIAnalysis; procedure TGLMFrm.ModelIIAnalysis(AReport: TStrings);
var var
block, i, j, NEntered, index, noblocks : integer; block, i, j, NEntered, index, noblocks : integer;
NLeft, NRight : integer; NLeft, NRight : integer;
cellstring : string; cellstring : string;
labelstr : string; labelstr : string;
begin begin
NEntered := 0; NEntered := 0;
OldR2 := 0; OldR2 := 0;
@@ -2252,7 +2252,7 @@ begin
NRight := NEntered - NLeft; NRight := NEntered - NLeft;
// call cancor routine for this block // call cancor routine for this block
cancor(NLeft,NRight,ColSelected); CanCor(NLeft, NRight, ColSelected, AReport);
end; // next block end; // next block
TypeIIProb := nil; TypeIIProb := nil;
@@ -2348,7 +2348,7 @@ begin
for j := 0 to NFixVecIndep[index]-1 do for j := 0 to NFixVecIndep[index]-1 do
begin begin
ColSelected[NEntered] := FixedIndepPos[index] + j; ColSelected[NEntered] := FixedIndepPos[index] + j;
labelstr := format('%s_%d',[FixedIndepCode.Items.Strings[index],j+1]); labelstr := Format('%s_%d', [FixedIndepCode.Items[index], j+1]);
Labels[NEntered] := labelstr; Labels[NEntered] := labelstr;
NEntered := NEntered + 1; NEntered := NEntered + 1;
end; end;
@@ -2368,7 +2368,7 @@ begin
for j := 0 to NRndVecIndep[index]-1 do for j := 0 to NRndVecIndep[index]-1 do
begin begin
ColSelected[NEntered] := RndIndepPos[index] + j; ColSelected[NEntered] := RndIndepPos[index] + j;
labelstr := format('%s_%d',[RndIndepCode.Items.Strings[index],j+1]); labelstr := Format('%s_%d', [RndIndepCode.Items[index], j+1]);
Labels[NEntered] := labelstr; Labels[NEntered] := labelstr;
NEntered := NEntered + 1; NEntered := NEntered + 1;
end; end;
@@ -2390,7 +2390,7 @@ begin
for j := 0 to NInteractVecs[i]-1 do for j := 0 to NInteractVecs[i]-1 do
begin begin
ColSelected[NEntered] := InteractPos[i] + j; ColSelected[NEntered] := InteractPos[i] + j;
labelstr := format('%s%d_%d',['IA',i+1,j+1]); labelstr := Format('%s%d_%d', ['IA',i+1,j+1]);
Labels[NEntered] := labelstr; Labels[NEntered] := labelstr;
NEntered := NEntered + 1; NEntered := NEntered + 1;
end; end;
@@ -2408,7 +2408,7 @@ begin
begin begin
index := i; // index of covariate code index := i; // index of covariate code
ColSelected[NEntered] := CovIndepPos[index]; ColSelected[NEntered] := CovIndepPos[index];
labelstr := format('%s',[CovariateCode.Items.Strings[index]]); labelstr := Format('%s', [CovariateCode.Items[index]]);
Labels[NEntered] := labelstr; Labels[NEntered] := labelstr;
NEntered := NEntered + 1; NEntered := NEntered + 1;
break; break;
@@ -2430,7 +2430,7 @@ begin
StdErrEst := sqrt(VarEst) StdErrEst := sqrt(VarEst)
else else
begin begin
ShowMessage('ERROR! Error in computing variance estimate.'); ErrorMsg('Error in computing variance estimate.');
StdErrEst := 0.0; StdErrEst := 0.0;
end; end;
@@ -2479,7 +2479,7 @@ begin
AReport.Add('SS for %-10s: %10.3f',[effstr,TypeISS[block]]); AReport.Add('SS for %-10s: %10.3f',[effstr,TypeISS[block]]);
AReport.Add('SS TOTAL: %10.3f',[SST]); AReport.Add('SS TOTAL: %10.3f',[SST]);
AReport.Add(''); AReport.Add('');
AReport.Add('======================================================================================='); AReport.Add(DIVIDER);
AReport.Add(''); AReport.Add('');
end; end;
@@ -2522,7 +2522,7 @@ begin
end; end;
AReport.Add('%20s %4.0f %10.3f %10.3f', ['Error Between', dferrbetween, sserrbetween, mserrbetween]); AReport.Add('%20s %4.0f %10.3f %10.3f', ['Error Between', dferrbetween, sserrbetween, mserrbetween]);
AReport.Add(''); AReport.Add('');
AReport.Add('======================================================================================='); AReport.Add(DIVIDER);
AReport.Add(''); AReport.Add('');
// Now, get within subject effects // Now, get within subject effects
@@ -2635,7 +2635,7 @@ begin
AReport.Add('SS for %-10s: %10.3f',[effstr, TypeIISS[block]]); AReport.Add('SS for %-10s: %10.3f',[effstr, TypeIISS[block]]);
AReport.Add('SS TOTAL: %10.3f',[SST]); AReport.Add('SS TOTAL: %10.3f',[SST]);
AReport.Add(''); AReport.Add('');
AReport.Add('======================================================================================='); AReport.Add(DIVIDER);
AReport.Add(''); AReport.Add('');
end; end;
@@ -2670,7 +2670,7 @@ begin
AReport.Add('%20s %4d %10.3f', ['TOTAL', totalobs-1, SST]); AReport.Add('%20s %4d %10.3f', ['TOTAL', totalobs-1, SST]);
AReport.Add(''); AReport.Add('');
AReport.Add('======================================================================================='); AReport.Add(DIVIDER);
AReport.Add(''); AReport.Add('');
// clean up the heap // clean up the heap
@@ -2954,7 +2954,7 @@ begin
datagrid[m,col] := datagrid[m,pos1] * datagrid[m,col] := datagrid[m,pos1] *
datagrid[m,pos2] * datagrid[m,pos3] * datagrid[m,pos2] * datagrid[m,pos3] *
datagrid[m,pos4] * datagrid[m,pos5]; datagrid[m,pos4] * datagrid[m,pos5];
cellstring := format('%s*%s*%s*%s*%s',[GenLabels[pos1], cellstring := Format('%s*%s*%s*%s*%s',[GenLabels[pos1],
GenLabels[pos2],GenLabels[pos3],GenLabels[pos4], GenLabels[pos2],GenLabels[pos3],GenLabels[pos4],
GenLabels[pos5]]); GenLabels[pos5]]);
GenLabels[col] := cellstring; GenLabels[col] := cellstring;
@@ -2967,11 +2967,10 @@ begin
end; // if listcnt = 3 end; // if listcnt = 3
end; end;
procedure TGLMFrm.CanCor(NLeft: integer; NRight: integer; GridPlace: IntDyneVec); procedure TGLMFrm.CanCor(NLeft: integer; NRight: integer; GridPlace: IntDyneVec;
label cleanup; AReport: TStrings);
var var
i, j, k, count, a_size, b_size, no_factors, IER: integer; i, j, k, count, a_size, b_size, no_factors, IER: integer;
outline: string;
s, m, n, df1, df2, q, w, pcnt_extracted, trace : double; s, m, n, df1, df2, q, w, pcnt_extracted, trace : double;
minroot, critical_prob, Lambda, Pillia : double; minroot, critical_prob, Lambda, Pillia : double;
chisqr, HLTrace, chiprob, ftestprob, Roys, f, Hroot : double; chisqr, HLTrace, chiprob, ftestprob, Roys, f, Hroot : double;
@@ -3067,16 +3066,16 @@ begin
selected[NLeft+i] := GridPlace[NLeft+i]; selected[NLeft+i] := GridPlace[NLeft+i];
end; end;
OutputFrm.RichEdit.Clear; AReport.Add('CANONICAL CORRELATION ANALYSIS');
OutputFrm.RichEdit.Lines.Add('CANONICAL CORRELATION ANALYSIS'); AReport.Add('');
OutputFrm.RichEdit.Lines.Add('');
count := NoCases; count := NoCases;
// Get means, standard deviations, etc. for total matrix // Get means, standard deviations, etc. for total matrix
IER := Dyncorrelations(novars,selected,datagrid,bigmat,mean,variance,stddev,totalobs,3); IER := DynCorrelations(novars,selected,datagrid,bigmat,mean,variance,stddev,totalobs,3);
if (IER = 1)then if (IER = 1) then
begin begin
ShowMessage('ERROR! Zero variance found for a variable-terminating'); ErrorMsg('Zero variance found for a variable-terminating');
goto cleanup; exit;
end; end;
//partition matrix into quadrants //partition matrix into quadrants
@@ -3098,13 +3097,15 @@ begin
if CorsChk.Checked then if CorsChk.Checked then
begin begin
title := 'Left Correlation Matrix'; title := 'Left Correlation Matrix';
MAT_PRINT(raa,NLeft,NLeft,title,a_vars,a_vars,totalobs); MatPrint(raa, NLeft, NLeft, title, a_vars, a_vars, totalobs, AReport);
title := 'Right Correlation Matrix'; title := 'Right Correlation Matrix';
MAT_PRINT(rbb,NRight,NRight,title,b_vars,b_vars,totalobs); MatPrint(rbb, NRight, NRight, title, b_vars, b_vars, totalobs, AReport);
title := 'Left-Right Correlation Matrix'; title := 'Left-Right Correlation Matrix';
MAT_PRINT(rab,NLeft,NRight,title,a_vars,b_vars,totalobs); MatPrint(rab, NLeft, NRight, title, a_vars, b_vars, totalobs, AReport);
OutputFrm.ShowModal;
OutputFrm.RichEdit.Clear; AReport.Add('');
AReport.Add(DIVIDER);
AReport.Add('');
end; end;
// get inverses of left and right hand matrices raa and rbb // get inverses of left and right hand matrices raa and rbb
@@ -3117,7 +3118,7 @@ begin
if CorsChk.Checked then if CorsChk.Checked then
begin begin
title := 'Inverse of Left Matrix'; title := 'Inverse of Left Matrix';
MAT_PRINT(raainv,a_size,a_size,title,a_vars,a_vars,totalobs); MatPrint(raainv, a_size, a_size, title, a_vars, a_vars, totalobs, AReport);
end; end;
for i := 0 to b_size-1 do for i := 0 to b_size-1 do
@@ -3129,7 +3130,7 @@ begin
if CorsChk.Checked then if CorsChk.Checked then
begin begin
title := 'Inverse of Right Matrix'; title := 'Inverse of Right Matrix';
MAT_PRINT(rbbinv,b_size,b_size,title,b_vars,b_vars,totalobs); MatPrint(rbbinv, b_size, b_size, title, b_vars, b_vars, totalobs, AReport);
end; end;
// get products of raainv x rab and the rbbinv x rba matrix // get products of raainv x rab and the rbbinv x rba matrix
@@ -3140,9 +3141,9 @@ begin
for j := 0 to b_size-1 do second_prod[i,j] := 0.0; for j := 0 to b_size-1 do second_prod[i,j] := 0.0;
MatAxB(second_prod,raainv,rab,a_size,a_size,a_size,b_size,errorcode); MatAxB(second_prod,raainv,rab,a_size,a_size,a_size,b_size,errorcode);
title := 'Right Inverse x Right-Left Matrix'; title := 'Right Inverse x Right-Left Matrix';
MAT_PRINT(first_prod,b_size,a_size,title,b_vars,a_vars,totalobs); MatPrint(first_prod, b_size, a_size, title, b_vars, a_vars, totalobs, AReport);
title := 'Left Inverse x Left-Right Matrix'; title := 'Left Inverse x Left-Right Matrix';
MAT_PRINT(second_prod,a_size,b_size,title,a_vars,b_vars,totalobs); MatPrint(second_prod, a_size, b_size, title, a_vars, b_vars, totalobs, AReport);
//get characteristic equations matrix (product of last two product matrices //get characteristic equations matrix (product of last two product matrices
//The product should yeild rows and cols representing the smaller of the two sets //The product should yeild rows and cols representing the smaller of the two sets
@@ -3150,9 +3151,11 @@ begin
for j := 0 to b_size - 1 do char_equation[i,j] := 0.0; for j := 0 to b_size - 1 do char_equation[i,j] := 0.0;
MatAxB(char_equation,first_prod,second_prod,b_size,a_size,a_size,b_size,errorcode); MatAxB(char_equation,first_prod,second_prod,b_size,a_size,a_size,b_size,errorcode);
title := 'Canonical Function'; title := 'Canonical Function';
MAT_PRINT(char_equation,b_size,b_size,title,CanLabels,CanLabels,totalobs); MatPrint(char_equation, b_size, b_size, title, CanLabels, CanLabels, totalobs, AReport);
OutputFrm.ShowModal;
OutputFrm.RichEdit.Clear; AReport.Add('');
AReport.Add(DIVIDER);
AReport.Add('');
// now get roots and vectors of the characteristic equation using // now get roots and vectors of the characteristic equation using
// NonSymRoots routine // NonSymRoots routine
@@ -3169,10 +3172,8 @@ begin
pcnt_trace, trace, pcnt_extracted); pcnt_trace, trace, pcnt_extracted);
outline := format('Trace of the matrix:=%10.4f',[trace]); AReport.Add('Trace of the matrix: %10.4f', [trace]);
OutputFrm.RichEdit.Lines.Add(outline); AReport.Add('Percent of trace extracted: %10.4f', [pcnt_extracted]);
outline := format('Percent of trace extracted: %10.4f',[pcnt_extracted]);
OutputFrm.RichEdit.Lines.Add(outline);
// Normalize smaller set weights and coumpute larger set weights // Normalize smaller set weights and coumpute larger set weights
for i := 0 to b_size - 1 do // transpose eigenvectors for i := 0 to b_size - 1 do // transpose eigenvectors
@@ -3266,24 +3267,20 @@ begin
end; end;
// Print remaining results // Print remaining results
OutputFrm.RichEdit.Lines.Add(''); AReport.Add('');
OutputFrm.RichEdit.Lines.Add(''); AReport.Add('');
outline := ' Canonical R Root % Trace Chi-Sqr D.F. Prob.'; AReport.Add(' Canonical R Root % Trace Chi-Sqr D.F. Prob.');
OutputFrm.RichEdit.Lines.Add(outline);
for i := 0 to b_size-1 do for i := 0 to b_size-1 do
begin AReport.Add('%2d %10.6f %8.3f %7.3f %8.3f %2d %8.3f',
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]]); [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;
chisqr := -ln(Lambda) * (count - 1.0 - 0.5 * (a_size + b_size - 1.0)); chisqr := -ln(Lambda) * (count - 1.0 - 0.5 * (a_size + b_size - 1.0));
chiprob := 1.0 - chisquaredprob(chisqr,a_size * b_size); chiprob := 1.0 - chisquaredprob(chisqr,a_size * b_size);
OutputFrm.RichEdit.Lines.Add(''); AReport.Add('');
OutputFrm.RichEdit.Lines.Add('Overall Tests of Significance:'); AReport.Add('Overall Tests of Significance:');
OutputFrm.RichEdit.Lines.Add(' Statistic Approx. Stat. Value D.F. Prob.>Value'); AReport.Add(' Statistic Approx. Stat. Value D.F. Prob.>Value');
outline := format('Wilk''s Lambda Chi-Squared %10.4f %3d %6.4f', AReport.Add('Wilk''s Lambda Chi-Squared %10.4f %3d %6.4f', [chisqr,a_size * b_size,chiprob]);
[chisqr,a_size * b_size,chiprob]);
OutputFrm.RichEdit.Lines.Add(outline);
s := b_size; s := b_size;
m := 0.5 * (a_size - b_size - 1); m := 0.5 * (a_size - b_size - 1);
n := 0.5 * (count - b_size - a_size - 2); n := 0.5 * (count - b_size - a_size - 2);
@@ -3291,78 +3288,80 @@ begin
df1 := s * (2.0 * m + s + 1.0); df1 := s * (2.0 * m + s + 1.0);
df2 := 2.0 * ( s * n + 1.0); df2 := 2.0 * ( s * n + 1.0);
ftestprob := probf(f,df1,df2); ftestprob := probf(f,df1,df2);
outline := format('Hotelling-Lawley Trace F-Test %10.4f %2.0f %2.0f %6.4f', AReport.Add('Hotelling-Lawley Trace F-Test %10.4f %2.0f %2.0f %6.4f', [f, df1, df2, ftestprob]);
[f, df1,df2, ftestprob]);
OutputFrm.RichEdit.Lines.Add(outline);
df2 := s * (2.0 * n + s + 1.0); df2 := s * (2.0 * n + s + 1.0);
f := (Pillia / (s - Pillia)) * ( (2.0 * n + s +1.0) / (2.0 * m + s + 1.0) ); f := (Pillia / (s - Pillia)) * ( (2.0 * n + s +1.0) / (2.0 * m + s + 1.0) );
ftestprob := probf(f,df1,df2); ftestprob := probf(f,df1,df2);
outline := format('Pillai Trace F-Test %10.4f %2.0f %2.0f %6.4f', AReport.Add('Pillai Trace F-Test %10.4f %2.0f %2.0f %6.4f', [f, df1, df2, ftestprob]);
[f, df1,df2, ftestprob]);
OutputFrm.RichEdit.Lines.Add(outline);
Roys := Roys * (count - 1 - a_size + b_size)/ a_size ; Roys := Roys * (count - 1 - a_size + b_size)/ a_size ;
df1 := a_size; df1 := a_size;
df2 := count - 1 - a_size + b_size; df2 := count - 1 - a_size + b_size;
ftestprob := probf(Roys,df1,df2); ftestprob := probf(Roys,df1,df2);
outline := format('Roys Largest Root F-Test %10.4f %2.0f %2.0f %6.4f', AReport.Add('Roys Largest Root F-Test %10.4f %2.0f %2.0f %6.4f', [Roys, df1, df2, ftestprob]);
[Roys, df1, df2, ftestprob]);
OutputFrm.RichEdit.Lines.Add(outline); AReport.Add('');
OutputFrm.ShowModal; AReport.Add(DIVIDER);
OutputFrm.RichEdit.Clear; AReport.Add('');
if CorsChk.Checked then if CorsChk.Checked then
begin begin
title := 'Eigenvectors'; title := 'Eigenvectors';
MAT_PRINT(eigenvectors,b_size,b_size,title,CanLabels,CanLabels,totalobs); MatPrint(eigenvectors, b_size, b_size, title, CanLabels, CanLabels, totalobs, AReport);
OutputFrm.ShowModal(); AReport.Add('');
OutputFrm.RichEdit.Clear; AReport.Add(DIVIDER);
AReport.Add('');
end; end;
title := 'Standardized Right Side Weights'; 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'; title := 'Standardized Left Side Weights';
MAT_PRINT(norm_b,b_size,b_size,title,ColLabels,CanLabels,totalobs); MatPrint(norm_b, b_size, b_size, title, ColLabels, CanLabels, totalobs, AReport);
OutputFrm.ShowModal;
AReport.Add('');
AReport.Add(DIVIDER);
AReport.Add('');
title := 'Raw Right Side Weights'; 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'; title := 'Raw Left Side Weights';
MAT_PRINT(raw_b,b_size,b_size,title,ColLabels,CanLabels,totalobs); MatPrint(raw_b, b_size, b_size, title, ColLabels, CanLabels, totalobs, AReport);
OutputFrm.ShowModal;
AReport.Add('');
AReport.Add(DIVIDER);
AReport.Add('');
title := 'Right Side Correlations with Function'; 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'; title := 'Left Side Correlations with Function';
MAT_PRINT(b_cors,b_size,b_size,title,ColLabels,CanLabels,totalobs); MatPrint(b_cors, b_size, b_size, title, ColLabels, CanLabels, totalobs, AReport);
OutputFrm.ShowModal;
OutputFrm.RichEdit.Clear; AReport.Add('');
AReport.Add(DIVIDER);
AReport.Add('');
if CorsChk.Checked then if CorsChk.Checked then
begin begin
outline := 'Redundancy Analysis for Right Side Variables'; AReport.Add('Redundancy Analysis for Right Side Variables');
OutputFrm.RichEdit.Lines.Add(outline); AReport.Add('');
OutputFrm.RichEdit.Lines.Add(''); AReport.Add(' Variance Prop. Redundancy');
outline := ' Variance Prop. Redundancy';
OutputFrm.RichEdit.Lines.Add(outline);
for i := 0 to b_size-1 do for i := 0 to b_size-1 do
begin AReport.Add('%10d %10.5f %10.5f', [i, pv_a[i], rd_a[i]]);
outline := format('%10d %10.5f %10.5f',[i,pv_a[i],rd_a[i]]); AReport.Add('');
OutputFrm.RichEdit.Lines.Add(outline); AReport.Add('Redundancy Analysis for Left Side Variables');
end; AReport.Add(' Variance Prop. Redundancy');
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);
for i := 0 to b_size-1 do for i := 0 to b_size-1 do
begin AReport.Add('%10d %10.5f %10.5f', [i, pv_b[i], rd_b[i]]);
outline := format('%10d %10.5f %10.5f',[i,pv_b[i],rd_b[i]]);
OutputFrm.RichEdit.Lines.Add(outline); AReport.Add('');
end; AReport.Add(DIVIDER);
OutputFrm.ShowModal; AReport.Add('');
OutputFrm.RichEdit.Clear;
end; end;
//------------- Now, clean up memory mess ---------------------------- //------------- Now, clean up memory mess ----------------------------
cleanup:
selected := nil; selected := nil;
ColLabels := nil; ColLabels := nil;
RowLabels := nil; RowLabels := nil;