public IntervalEstimation IntervalDistribution(double[] xArray, int[] vArray, double reponseProbability, double confidenceLevel)
{
var outputParameters = MLS_getMLS(xArray, vArray);
MLR_polar.Likelihood_Ratio_Polar(xArray, vArray, "normal", outputParameters.μ0_final, outputParameters.σ0_final, reponseProbability, confidenceLevel, out var final_result);
return(IntervalEstimation.Parse(final_result));
}
public override IntervalEstimation IntervalDistribution(double[] xArray, int[] vArray, double reponseProbability, double confidenceLevel)
{
MLR_polar.Max_Likelihood_Estimate(xArray, vArray, "logistic", out var mu, out var sigma, out var L);
MLR_polar.Likelihood_Ratio_Polar(xArray, vArray, "logistic", mu, sigma, reponseProbability, confidenceLevel, out var final_result);
IntervalEstimation ret = new IntervalEstimation();
ret.Confidence.Down = final_result[5];
ret.Confidence.Up = final_result[4];
ret.Mu.Down = final_result[1];
ret.Mu.Up = final_result[0];
ret.Sigma.Down = final_result[3];
ret.Sigma.Up = final_result[2];
return(ret);
}
public override IntervalEstimation IntervalDistribution(double[] xArray, int[] vArray, double reponseProbability, double confidenceLevel)
{
OutputParameters outputParameters = new OutputParameters();
pub_function.norm_MLS_getMLS(xArray, vArray, out outputParameters.varmu, out outputParameters.varsigma, out outputParameters.Maxf, out outputParameters.Mins);
MLR_polar.Likelihood_Ratio_Polar(xArray, vArray, "normal", outputParameters.varmu, outputParameters.varsigma, reponseProbability, confidenceLevel, out var final_result);
IntervalEstimation ret = new IntervalEstimation();
ret.Confidence.Down = final_result[5];
ret.Confidence.Up = final_result[4];
ret.Mu.Down = final_result[1];
ret.Mu.Up = final_result[0];
ret.Sigma.Down = final_result[3];
ret.Sigma.Up = final_result[2];
return(ret);
}
public IntervalEstimation IntervalDistribution(double[] xArray, int[] vArray, double reponseProbability, double confidenceLevel, double favg, double fsigma)
{
MLR_polar.Likelihood_Ratio_Polar(xArray, vArray, "logistic", favg, fsigma, reponseProbability, confidenceLevel, out var final_result);
return(IntervalEstimation.Parse(final_result));
}
