/// <summary>
/// The likelihood ratio test of the overall model, also called the model chi-square test.
/// </summary>
///
/// <param name="input">A set of input data.</param>
/// <param name="time">The time-to-event before the output occurs.</param>
/// <param name="output">The corresponding output data.</param>
///
/// <remarks>
/// <para>
/// The Chi-square test, also called the likelihood ratio test or the log-likelihood test
/// is based on the deviance of the model (-2*log-likelihood). The log-likelihood ratio test
/// indicates whether there is evidence of the need to move from a simpler model to a more
/// complicated one (where the simpler model is nested within the complicated one).</para>
/// <para>
/// The difference between the log-likelihood ratios for the researcher's model and a
/// simpler model is often called the "model chi-square".</para>
/// </remarks>
///
public ChiSquareTest ChiSquare(double[][] input, double[] time, SurvivalOutcome[] output)
{
ProportionalHazards regression = new ProportionalHazards(Inputs);
double ratio = GetLogLikelihoodRatio(input, time, output, regression);
return(new ChiSquareTest(ratio, Coefficients.Length));
}
/// <summary>
/// Creates a new Cox's Proportional Hazards that is a copy of the current instance.
/// </summary>
///
public object Clone()
{
var regression = new ProportionalHazards(Coefficients.Length);
regression.Coefficients = (double[])this.Coefficients.Clone();
regression.StandardErrors = (double[])this.StandardErrors.Clone();
regression.Offsets = (double[])this.Offsets.Clone();
return(regression);
}
/// <summary>
/// Gets the Log-Likelihood Ratio between two models.
/// </summary>
///
/// <remarks>
/// The Log-Likelihood ratio is defined as 2*(LL - LL0).
/// </remarks>
///
/// <param name="input">A set of input data.</param>
/// <param name="time">The time-to-event before the output occurs.</param>
/// <param name="output">The corresponding output data.</param>
/// <param name="hazards">Another Cox Proportional Hazards model.</param>
///
/// <returns>The Log-Likelihood ratio (a measure of performance
/// between two models) calculated over the given data sets.</returns>
///
public double GetLogLikelihoodRatio(double[][] input, double[] time, SurvivalOutcome[] output, ProportionalHazards hazards)
{
return(2.0 * (this.GetPartialLogLikelihood(input, time, output) - hazards.GetPartialLogLikelihood(input, time, output)));
}
