} //# end of sqrt.invertedGamma.gen
//rgamma.truncated <- function(alpha, beta, range)
public static double RGammaTruncated(double alpha, double beta, double[] range)
{
//# We first look on which side of the distribution (comparing to its mode)
//# the range lies, in order to decide on which side we will compute the log.prob
//# (choosing the correct side gives more accuracy in the sampling in the eventuality of a remote range)
bool lowerTail = false;
if (alpha < 1)
{
lowerTail = false;
}
else
{
double mode = (alpha - 1) / beta;
double minRange = range.Min();
double maxRange = range.Max();
if (minRange > mode)
{
lowerTail = false;
}
else if (maxRange < mode)
{
lowerTail = true;
}
else
{
double logPLeft = GammaDistribution.PGammaFromRateParameter(x: minRange, alph: alpha, rate: beta, logP: true, lowerTail: true);
double logPRight = GammaDistribution.PGammaFromRateParameter(x: maxRange, alph: alpha, rate: beta, logP: true, lowerTail: false);
lowerTail = logPLeft < logPRight;
}
}
double[] logPLim = GammaDistribution.PGammaFromRateParameter(x: range, alph: alpha, rate: beta, lowerTail: lowerTail, logP: true);
double logP = RNorm4CensoredMeasures.RUnifLogP1(logPLim, lowerTail: lowerTail);
return(GammaDistribution.QGammaFromRate(logP, shape: alpha, rate: beta, logP: true, lowerTail: lowerTail));
}
