private SideReturnData GetSideReturnDataValue(double Y_Ceiling, double Y_LowerLimit, int Y_PartitionNumber)
{
SideReturnData sideReturnData = new SideReturnData();
double Y_ScaleLength = (LiftingDistributionSelection.QValue(Y_Ceiling) - LiftingDistributionSelection.QValue(Y_LowerLimit)) / Y_PartitionNumber;
sideReturnData.responseProbability = new double[Y_PartitionNumber + 1];
for (int i = 0; i <= Y_PartitionNumber; i++)
{
if (i == 0)
{
sideReturnData.responseProbability[i] = Y_LowerLimit;
}
else
{
sideReturnData.responseProbability[i] = LiftingDistributionSelection.PValue(LiftingDistributionSelection.QValue(Y_LowerLimit) + i * Y_ScaleLength, 0, 1);
}
}
sideReturnData.Y_Ceilings = new double[sideReturnData.responseProbability.Length];
sideReturnData.Y_LowerLimits = new double[sideReturnData.responseProbability.Length];
sideReturnData.responsePoints = new double[sideReturnData.responseProbability.Length];
return(sideReturnData);
}
public double ResponsePointCalculate(double fq, double favg, double fsigma) => LiftingMethodStandardSelection.ProcessValue(LiftingMethodStandardSelection.InverseProcessValue(favg) + (LiftingDistributionSelection.QValue(fq) * fsigma));
//计算多组试验结果
public MultigroupTest MultigroupTestResult(int[] nj, double[] Gj, double[] Hj, double[] muj, double[] sigmaj)
{
int nfinal = 0;
var multigroupTest = get_multiGroup_result(nj, muj, sigmaj, Gj, Hj, out nfinal);
double f001 = Math.Sqrt(Math.Pow(multigroupTest.Sigma_mu, 2) + Math.Pow(multigroupTest.Sigma_sigma, 2) * Math.Pow(LiftingDistributionSelection.QValue(0.001), 2));
pub_function.resolution_getReso(f001, 0.000001, out multigroupTest.prec01);
double f999 = Math.Sqrt(Math.Pow(multigroupTest.Sigma_mu, 2) + Math.Pow(multigroupTest.Sigma_sigma, 2) * Math.Pow(LiftingDistributionSelection.QValue(0.999), 2));
pub_function.resolution_getReso(f999, 0.000001, out multigroupTest.prec999);
double p001 = LiftingMethodStandardSelection.ProcessValue(LiftingMethodStandardSelection.InverseProcessValue(multigroupTest.μ0_final) - LiftingDistributionSelection.DistributionProcess() * multigroupTest.σ0_final);
pub_function.resolution_getReso(p001, 0.000001, out multigroupTest.rpse01);
double p999 = LiftingMethodStandardSelection.ProcessValue(LiftingMethodStandardSelection.InverseProcessValue(multigroupTest.μ0_final) + LiftingDistributionSelection.DistributionProcess() * multigroupTest.σ0_final);
pub_function.resolution_getReso(p999, 0.000001, out multigroupTest.rpse999);
return(multigroupTest);
}
//拟然比法区间计算绘图
public SideReturnData QuasiLikelihoodRatioMethod(double Y_Ceiling, double Y_LowerLimit, int Y_PartitionNumber, double ConfidenceLevel, double favg, double fsigma, double[] xArray, int[] vArray, int intervalChoose)
{
var sideReturnData = GetSideReturnDataValue(Y_Ceiling, Y_LowerLimit, Y_PartitionNumber);
xArray = LiftingMethodStandardSelection.InverseProcessArray(xArray);
for (int i = 0; i < sideReturnData.responseProbability.Length; i++)
{
IntervalEstimation ie = new IntervalEstimation();
if (intervalChoose == 0)
{
ie = GetIntervalEstimationValue(SingleSideEstimation(xArray, vArray, sideReturnData.responseProbability[i], ConfidenceLevel, LiftingMethodStandardSelection.InverseProcessValue(favg), fsigma));
}
else
{
ie = GetIntervalEstimationValue(DoubleSideEstimation(xArray, vArray, sideReturnData.responseProbability[i], ConfidenceLevel, LiftingMethodStandardSelection.InverseProcessValue(favg), fsigma));
}
sideReturnData.Y_LowerLimits[i] = ie.Confidence.Down;
sideReturnData.Y_Ceilings[i] = ie.Confidence.Up;
double fq = sideReturnData.responseProbability[i];
sideReturnData.responsePoints[i] = LiftingMethodStandardSelection.ProcessValue(LiftingMethodStandardSelection.InverseProcessValue(favg) + LiftingDistributionSelection.QValue(fq) * fsigma);
}
return(sideReturnData);
}
private double[] GetDoubleArray(double Tfw, double Tfw_dance, double fq, double favg, double fsigma, double fsigmaavg, double fsigmasigma)
{
double[] ie = new double[8];
ie[0] = LiftingMethodStandardSelection.ProcessValue(LiftingMethodStandardSelection.InverseProcessValue(favg) + LiftingDistributionSelection.QValue(fq) * fsigma + Tfw * Math.Sqrt(Math.Pow(fsigmaavg, 2) + Math.Pow(fsigmasigma, 2) * Math.Pow(LiftingDistributionSelection.QValue(fq), 2)));
ie[1] = LiftingMethodStandardSelection.ProcessValue(LiftingMethodStandardSelection.InverseProcessValue(favg) + LiftingDistributionSelection.QValue(fq) * fsigma - Tfw * Math.Sqrt(Math.Pow(fsigmaavg, 2) + Math.Pow(fsigmasigma, 2) * Math.Pow(LiftingDistributionSelection.QValue(fq), 2)));
ie[2] = LiftingMethodStandardSelection.ProcessValue(LiftingMethodStandardSelection.InverseProcessValue(favg) + LiftingDistributionSelection.QValue(fq) * fsigma + Tfw_dance * Math.Sqrt(Math.Pow(fsigmaavg, 2) + Math.Pow(fsigmasigma, 2) * Math.Pow(LiftingDistributionSelection.QValue(fq), 2)));
ie[3] = LiftingMethodStandardSelection.ProcessValue(LiftingMethodStandardSelection.InverseProcessValue(favg) + LiftingDistributionSelection.QValue(fq) * fsigma - Tfw_dance * Math.Sqrt(Math.Pow(fsigmaavg, 2) + Math.Pow(fsigmasigma, 2) * Math.Pow(LiftingDistributionSelection.QValue(fq), 2)));
ie[4] = LiftingMethodStandardSelection.ProcessValue(LiftingMethodStandardSelection.InverseProcessValue(favg) + Tfw * fsigmaavg);
ie[5] = LiftingMethodStandardSelection.ProcessValue(LiftingMethodStandardSelection.InverseProcessValue(favg) - Tfw * fsigmaavg);
ie[6] = fsigma + Tfw * fsigmasigma;
ie[7] = fsigma - Tfw * fsigmasigma;
return(ie);
}
//响应点计算
public double ResponsePointCalculation(double fq, double fsimga, double favg)
{
double rpc = LiftingMethodStandardSelection.ProcessValue(LiftingMethodStandardSelection.InverseProcessValue(favg) + LiftingDistributionSelection.QValue(fq) * fsimga);
pub_function.resolution_getReso(rpc, 0.000001, out rpc);
return(rpc);
}
public double[] ResponsePointStandardError(double Sigma_mu, double Sigma_sigma)
{
double[] rpse = new double[2];
rpse[0] = pub_function.resolution_getReso(Math.Sqrt(Math.Pow(Sigma_mu, 2) + Math.Pow(Sigma_sigma, 2) * Math.Pow(LiftingDistributionSelection.QValue(0.001), 2)), 0.000001);
rpse[1] = pub_function.resolution_getReso(Math.Sqrt(Math.Pow(Sigma_mu, 2) + Math.Pow(Sigma_sigma, 2) * Math.Pow(LiftingDistributionSelection.QValue(0.999), 2)), 0.000001);
return(rpse);
}