private double TrueValueGen(GenObject genO, MeasurementError me, double y, double mu, double logY)
{
SGNFnAParam localA = genO.A.Clone();
localA.Mu = mu;
if (genO.LogNormalDistrn)
{
localA.LogY = logY;
}
localA.Y = y;
localA.Y2 = y * y;
if (genO.ThroughSD)
{
localA.Ksi = me.Parm;
localA.Ksi2 = me.Parm * me.Parm;
}
else
{
localA.CV2 = me.Parm * me.Parm;
}
double[] start = genO.Start(localA);
//start.Any(zz => !zz.IsFinite());
Icdf icdf = new Icdf(genO, localA, range: genO.Range);
double x = icdf.Bidon(start, inestLowerLim: !genO.LogNormalDistrn);
if (genO.LogNormalDistrn)
{
x = Math.Exp(x);// # new_0.11
}
return(x);
} //# end of truevalue.gen
internal static MEParmGen GetInstance(GenObject o, MeasurementError me, DataSummary data, YGen genY, TrueValuesGen genTV)
{
MEParmGen instance = new MEParmGen();
double b;
double[] tmpY, tmpT;
if (me.ThroughCV)
{
if (o.LogNormalDistrn)
{
tmpY = Tools.Combine(data.LogY, genY.LogGT, genY.LogLT, genY.LogI);
tmpT = Tools.Combine(genTV.LogY, genTV.LogGT, genTV.LogLT, genTV.LogI);
b = tmpY.Substract(tmpT).Exp().Substract(1.0).Sqr().Sum();
b /= 2.0;
}
else
{
tmpY = Tools.Combine(data.Y, genY.GT, genY.LT, genY.I);
tmpT = Tools.Combine(genTV.Y, genTV.GT, genTV.LT, genTV.I);
b = tmpY.Divide(tmpT).Substract(1.0).Sqr().Reverse().Sum();
b /= 2.0;
}
SGNFnAParam localA = o.A.Clone();
localA.B = b;
localA.Range = me.GetRange();
double[] range = me.GetRange();
Icdf icdf = new Icdf(o, localA, range);
instance.Parm = icdf.Bidon(o.Start(localA), inestLowerLim: range[0] == 0);
}
else
{
tmpY = Tools.Combine(data.Y, genY.GT, genY.LT, genY.I);
tmpT = Tools.Combine(genTV.Y, genTV.GT, genTV.LT, genTV.I);
b = tmpY.Substract(tmpT).Sqr().Sum();
b /= 2.0;
if (o.LogNormalDistrn)
{
SGNFnAParam localA = o.A.Clone();
localA.B = b;
localA.Range = me.GetRange();
localA.Truevalues = Tools.Copy(tmpT);
//me.parm <- dens.gen.icdf(o, A, range=me$range, inestimable.lower.limit=me$range[1]==0)
double[] range = me.GetRange();
Icdf icdf = new Icdf(o, localA, range);
instance.Parm = icdf.Bidon(inestLowerLim: range[0] == 0.0);
}
else
{
instance.Parm = WebExpoFunctions3.SqrtInvertedGammaGen(data.N, b, me.GetRange(), o);
}
}
return(instance);
}
/*
* Pour ME_Gen Objects
*/
internal static GenObject GetMeGenObject(MeasurementError me, bool logNDstrn, int N)
{
if (me.ThroughCV)
{
return(new ME_CV_GenObject(N, logNDstrn));
}
else
{
// me.ThroughSD est vrai
return(null);
}
}
private YGen(MeasurementError me, TrueValuesGen genTV, DataSummary data, double mu, double sigma, bool logNormalDistrn = true)
{
if (me.Any)
{
// Sample y (censored) values | true values
if (data.AnyGT)
{
double[] tmpMean = genTV.GT;
double[] tmpSD;
if (me.ThroughCV)
{
tmpSD = tmpMean.Multiply(me.Parm);
}
else
{
tmpSD = Tools.Rep(me.Parm, tmpMean.Length);
}
this.GT = RNorm4CensoredMeasures.RNormCensored(tmpMean, tmpSD, lower: data.GT);
if (logNormalDistrn)
{
this.LogGT = this.GT.Log();
}
}
if (data.AnyLT)
{
double[] tmpMean = genTV.LT;
double[] tmpSD;
if (me.ThroughCV)
{
tmpSD = tmpMean.Multiply(me.Parm);
}
else
{
tmpSD = Tools.Rep(me.Parm, tmpMean.Length);
}
this.I = RNorm4CensoredMeasures.RNormCensored(tmpMean, tmpSD, upper: data.LT, negativeDisallowed: logNormalDistrn || me.ThroughCV);
if (logNormalDistrn)
{
this.LogLT = this.LT.Log();
}
}
if (data.AnyIntervalCensored)
{
double[] tmpMean = genTV.I;
double[] tmpSD;
if (me.ThroughCV)
{
tmpSD = tmpMean.Multiply(me.Parm);
}
else
{
tmpSD = Tools.Rep(me.Parm, tmpMean.Length);
}
this.I = RNorm4CensoredMeasures.RNormCensored(tmpMean, tmpSD, lower: data.IntervalGT, upper: data.IntervalLT);
if (logNormalDistrn)
{
this.LogI = this.I.Log();
}
}
}
else
{
if (logNormalDistrn)
{
if (data.AnyGT)
{
this.LogGT = RNorm4CensoredMeasures.RNormCensored(mu, sigma, lower: data.LogGT);
this.GT = this.LogGT.Exp();
}
if (data.AnyLT)
{
this.LogLT = RNorm4CensoredMeasures.RNormCensored(mu, sigma, upper: data.LogLT);
this.LT = this.LogLT.Exp();
}
if (data.AnyIntervalCensored)
{
this.LogI = RNorm4CensoredMeasures.RNormCensored(mu, sigma, lower: data.LogIntervalGT, upper: data.LogIntervalLT);
this.I = this.LogI.Exp();
}
}
else
{
if (data.AnyGT)
{
this.GT = RNorm4CensoredMeasures.RNormCensored(mu, sigma, lower: data.GT);
}
if (data.AnyLT)
{
this.LT = RNorm4CensoredMeasures.RNormCensored(mu, sigma, upper: data.LT);
}
if (data.AnyIntervalCensored)
{
this.I = RNorm4CensoredMeasures.RNormCensored(mu, sigma, lower: data.IntervalGT, upper: data.IntervalLT);
}
}
}
}// internal YGen (constructor)
public static YGen GetInstance(MeasurementError me, TrueValuesGen genTV, DataSummary data, double mu, double sigma, bool logNormalDistrn = true)
{
if (me.Any)
{
YGen newYGen = new YGen();
// Sample y (censored) values | true values
if (data.AnyGT)
{
double[] tmpMean = genTV.GT;
double[] tmpSD;
if (me.ThroughCV)
{
tmpSD = tmpMean.Multiply(me.Parm);
}
else
{
tmpSD = Tools.Rep(me.Parm, tmpMean.Length);
}
newYGen.GT = RNorm4CensoredMeasures.RNormCensored(tmpMean, tmpSD, lower: data.GT);
if (logNormalDistrn)
{
newYGen.LogGT = newYGen.GT.Log();
}
}
if (data.AnyLT)
{
double[] tmpMean = genTV.LT;
double[] tmpSD;
if (me.ThroughCV)
{
tmpSD = tmpMean.Multiply(me.Parm);
}
else
{
tmpSD = Tools.Rep(me.Parm, tmpMean.Length);
}
newYGen.LT = RNorm4CensoredMeasures.RNormCensored(tmpMean, tmpSD, upper: data.LT, negativeDisallowed: logNormalDistrn || me.ThroughCV);
if (logNormalDistrn)
{
newYGen.LogLT = newYGen.LT.Log();
}
}
if (data.AnyIntervalCensored)
{
double[] tmpMean = genTV.I;
double[] tmpSD;
if (me.ThroughCV)
{
tmpSD = tmpMean.Multiply(me.Parm);
}
else
{
tmpSD = Tools.Rep(me.Parm, tmpMean.Length);
}
newYGen.I = RNorm4CensoredMeasures.RNormCensored(tmpMean, tmpSD, lower: data.IntervalGT, upper: data.IntervalLT);
if (logNormalDistrn)
{
newYGen.LogI = newYGen.I.Log();
}
}
return(newYGen);
}
else
{
return(YGen.Inits(data, mu, sigma, meThroughCV: data.METhroughCV, logNormalDistrn: logNormalDistrn));
}
}
private TrueValuesGen(YGen genY, DataSummary data, double mu, double sigma, MeasurementError me, bool logNormalDistrn = true, GenObject o = null)
{
if (me.ThroughSD && !logNormalDistrn)
{
double meSD = me.Parm;
double tauStar = 1 / Math.Pow(sigma, 2) + 1 / Math.Pow(meSD, 2);
double sdStar = 1 / Math.Sqrt(tauStar);
if (data.YLength > 0)
{
double[] tmpMean = (data.Y.Divide(Math.Pow(meSD, 2)).Add(mu / Math.Pow(sigma, 2))).Divide(tauStar);
this.Y = NormalDistribution.RNorm(data.YLength, tmpMean, Tools.Rep(sdStar, tmpMean.Length));
}
if (data.GTLength > 0)
{
double[] tmpMean = (genY.GT.Divide(Math.Pow(meSD, 2)).Add(mu / Math.Pow(sigma, 2))).Divide(tauStar);
this.Y = NormalDistribution.RNorm(data.GTLength, tmpMean, Tools.Rep(sdStar, tmpMean.Length));
}
if (data.LTLength > 0)
{
double[] tmpMean = (genY.LT.Divide(Math.Pow(meSD, 2)).Add(mu / Math.Pow(sigma, 2))).Divide(tauStar);
this.Y = NormalDistribution.RNorm(data.GTLength, tmpMean, Tools.Rep(sdStar, tmpMean.Length));
}
if (data.IntervalLength > 0)
{
double[] tmpMean = (genY.I.Divide(Math.Pow(meSD, 2)).Add(mu / Math.Pow(sigma, 2))).Divide(tauStar);
this.Y = NormalDistribution.RNorm(data.GTLength, tmpMean, Tools.Rep(sdStar, tmpMean.Length));
}
}
else
{
o.A.Sigma2 = sigma * sigma;
this.Y = new double[data.YLength];
this.GT = new double[data.GTLength];
this.LT = new double[data.LTLength];
this.I = new double[data.IntervalLength];
for (int j = 0; j < data.YLength; j++)
{
this.Y[j] = TrueValueGen(o, me, data.Y[j], mu, logY: logNormalDistrn?data.LogY[j] : Tools.ND);
}
for (int j = 0; j < data.GTLength; j++)
{
this.GT[j] = TrueValueGen(o, me, genY.GT[j], mu, logY: logNormalDistrn?genY.LogGT[j] : Tools.ND);
}
for (int j = 0; j < data.LTLength; j++)
{
this.LT[j] = TrueValueGen(o, me, genY.LT[j], mu, logY: logNormalDistrn?genY.LogLT[j] : Tools.ND);
}
for (int j = 0; j < data.IntervalLength; j++)
{
this.I[j] = TrueValueGen(o, me, genY.I[j], mu, logY: logNormalDistrn?genY.LogI[j] : Tools.ND);
}
if (logNormalDistrn)
{
this.LogY = this.Y.Log();
this.LogGT = this.GT.Log();
this.LogLT = this.LT.Log();
this.LogI = this.I.Log();
}
}
} //# end of truevalues.gen
} //# end of truevalues.gen
internal static TrueValuesGen GetInstance(YGen genY, DataSummary data, double mu, double sigma, MeasurementError me, bool logNormalDistrn = true, GenObject o = null)
{
return(new TrueValuesGen(genY, data, mu, sigma, me, logNormalDistrn, o));
}
private void AddME(string me)
{
string x = Regex.Replace(me, @" ", "");
if (x.Length < 5)
{
return;
}
string meType = x.Substring(0, 2).ToLower();
if (meType != "sd" && meType != "cv")
{
return;
}
if (x[2] != '(')
{
return;
}
if (x.Last() != ')')
{
return;
}
string str = x.Substring(3, x.Length - 4);
if (str == string.Empty)
{
return;
}
string[] numbers = str.Split(new char[] { '~' }, StringSplitOptions.RemoveEmptyEntries);
if ((numbers.Length == 0) || (numbers.Length > 2))
{
return;
}
double a, b;
bool test;
test = ParseDouble(numbers[0], out a);
if (!test)
{
return;
}
b = a;
if (numbers.Length == 2)
{
test = ParseDouble(numbers[1], out b);
if (!test)
{
return;
}
}
if (a > b)
{
Error.AddError(string.Format("({0}, {1}) do not represent a valid range for the measurement error.", a, b), this.ClassName);
return;
}
this.ME = (meType == "sd") ? MeasurementError.NewSDError(a, b) : MeasurementError.NewCVError(a, b);
return;
}
