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)); }