lazarus-ccr/applications/lazstats/tests/multiple_regression_test/multiple_regression.lpr

program multiple_regression;

uses
  SysUtils, Classes,
  Globals, MatrixUnit, RegressionUnit;

var
  L: TStrings;
  xCols: IntDyneVec = nil;
  yCol: Integer;
  xData: TDblMatrix = nil;
  yData: TDblVector = nil;
  i, j: Integer;
  sa: TStringArray = nil;
  RegressionRes: TMultipleRegressionResults;
  Labels: StrDyneVec = nil;

const
  W = 20;
  D = 3;

procedure WriteMatrix(A: TDblMatrix; RowLabels, ColLabels: StrDyneVec);
  var
    i,j: Integer;
    n, m: Integer;
  begin
    MatSize(A, n,m);

    Write('':W);
    for j := 0 to High(ColLabels) do
      Write(ColLabels[j]:W);
    WriteLn;

    for i := 0 to n-1 do
    begin
      Write(RowLabels[i]:W);
      for j := 0 to m-1 do
        Write(A[i,j]:W:D);
      WriteLn;
    end;
  end;

begin
  DefaultFormatSettings.DecimalSeparator := '.';
  SetLength(xCols, 2);
  xCols[0] := 0;
  xCols[1] := 1;

  yCol := 5;

  SetLength(Labels, Length(xCols) + 1);
  Labels[High(Labels)] := 'Intercept';

  L := TStringList.Create;
  try
    L.LoadFromFile('..\..\data\cansas.tab');

    sa := L[0].Split(#9);
    for j := 0 to High(xCols) do
      Labels[j] := sa[xCols[j]];

    SetLength(xData, L.Count-1, 2);
    SetLength(yData, L.Count-1);
    for i:=1 to L.Count-1 do
    begin
      sa := L[i].Split(#9);
      for j := 0 to High(xCols) do
        xData[i-1, xCols[j]] := StrToFloat(sa[xCols[j]]);
      yData[i-1] := StrToFloat(sa[yCol]);
    end;

    Write('Index':10);
    for j := 0 to High(xCols) do
      Write(Labels[j]:10);
    WriteLn(sa[yCol]:10);

    //WriteLn('Index':10, sa[0]:10, sa[1]:10, sa[yCol]:10);
    for i := 0 to High(yData) do
    begin
      Write(i:10);
      for j := 0 to High(xCols) do
        Write(xdata[i, j]:10:3);
      WriteLn(yData[i]:10:3);
    end;
    WriteLn;
  finally
    L.Free;
  end;

  MultipleRegression(xData, yData, 0.95, RegressionRes);

  for i := 0 to High(Labels) do
    WriteLn('B[' + Labels[i] + '] =':20, RegressionRes.Coeffs[i]:W:D);
  WriteLn;

  WriteLn('Variance-Covariance Matrix');
  WriteMatrix(RegressionRes.VarCovar, Labels, Labels);
  ReadLn;
end.