public static ILinkFunction GetLinkFunction(GlmDistributionFamily distribution)
{
switch (distribution)
{
case GlmDistributionFamily.Bernouli:
case GlmDistributionFamily.Binomial:
case GlmDistributionFamily.Categorical:
case GlmDistributionFamily.Multinomial:
return(new LogitLinkFunction());
case GlmDistributionFamily.Exponential:
case GlmDistributionFamily.Gamma:
return(new InverseLinkFunction());
case GlmDistributionFamily.InverseGaussian:
return(new InverseSquaredLinkFunction());
case GlmDistributionFamily.Normal:
return(new IdentityLinkFunction());
case GlmDistributionFamily.Poisson:
return(new LogLinkFunction());
default:
throw new NotImplementedException();
}
}
public GlmIrls(GlmDistributionFamily distribution, double[,] A, double[] b)
: base(distribution)
{
this.A = new SparseMatrix(A);
this.b = new SparseVector(b);
this.At = this.A.Transpose();
this.mStats = new Statistics.GlmStatistics(A.GetLength(1), b.Length);
}
public GlmIrlsSvdNewton(GlmDistributionFamily distribution, ILinkFunction linkFunc, double[,] A, double[] b)
: base(distribution, linkFunc, null, null, null)
{
this.A = new SparseMatrix(A);
this.b = new SparseVector(b);
this.At = this.A.Transpose();
this.mStats = new Statistics.GlmStatistics(A.GetLength(1), b.Length);
}
public Glm(GlmDistributionFamily distribution, double[][] A, double[] b, SingleTrajectoryContinuousSolver solver)
{
this.solver = solver;
this.mDistributionFamily = distribution;
this.mLinkFunc = GetLinkFunction(distribution);
this.A = A;
this.b = b;
this.mStats = new Statistics.GlmStatistics(A[0].Length, b.Length);
}
/// <summary>
/// Return the likelihood value of the fitted regression model
/// </summary>
/// <param name="data"></param>
/// <param name="beta_hat">estimated predictor coefficient in the fitted regression model</param>
/// <returns></returns>
public static double GetLikelihood(GlmDistributionFamily distribution, List <RDataRecord> data, double[] beta_hat)
{
switch (distribution)
{
case GlmDistributionFamily.Normal:
return(GetLikelihood_Normal(data, beta_hat));
default:
throw new NotImplementedException();
}
}
public Glm(GlmDistributionFamily distribution, double[,] A, double[] b, SingleTrajectoryContinuousSolver solver, int maxIters = -1)
{
this.solver = solver;
this.mDistributionFamily = distribution;
this.mLinkFunc = GetLinkFunction(distribution);
this.A = new double[A.GetLength(0)][];
for (int i = 0; i < A.GetLength(0); i++)
{
this.A[i] = new double[A.GetLength(1)];
for (int j = 0; j < A.GetLength(1); j++)
{
this.A[i][j] = A[i, j];
}
}
this.b = b;
if (maxIters > 0)
{
this.mMaxIters = maxIters;
}
this.mStats = new Statistics.GlmStatistics(A.GetLength(1), b.Length);
}
public Glm(GlmDistributionFamily distribution)
{
this.mLinkFunc = GetLinkFunction(distribution);
this.mDistributionFamily = distribution;
}
