Regress.LogisticRegress Method (TVec, TVec, TVec, TMtx, TSample, TVec, TVec, TSample)

Logistic regression.

public LogisticRegress(TVec y, TVec n, TVec b, TMtx A, double Offset, TVec YCalc, TVec BStd, double Tolerance);

Parameters

Parameters	Description
y	response vector containing binomial counts.
n	number of trials for each count. Y is assumed to be binomial(p,N).
b	regression parameter estimates.
A	matrix of covariates, including the constant vector if required.
Offset	offset if required.
YCalc	fitted values.
BStd	Regression parameter estimates errors.This is an estimate of the precision of the B estimates.
Tolerance	Default precision for reweighted LQR.

Remarks

Fit logistic regression model.

C# Example

The following example calculates coefficients for simple logistic regression. The counts are out of 10 in each case and there is one covariate[1].

using Dew.Math;
using Dew.Stats;
using Dew.Stats.Units;
namespace Dew.Examples
{
  private void Example()
  {
    Vector y = new Vector(0);
    Vector n = new Vector(0);
    Vector B = new Vector(0);
    Matrix X = new Matrix(0,0);
    y.SetIt(false,new double[] {2,0,3,1,5,5,6,9,5,9});
    n.Size(y);
    n.SetVal(10.0);
    X.SetIt(false,10,2, new double[]
          {1,1,
          1,2,
          1,3,
          1,4,
          1,5,
          1,6,
          1,7,
          1,8,
          1,9,
          1,10});
    Regress.LogisticRegress(y,n,B,null);
    // B = (-2.58,0.42)
  }
}