int DiscreteGamma (double freqK[], double rK[],
double alfa, double beta, int K, int median)
{
/* discretization of gamma distribution with equal proportions in each
category
*/
int i;
double gap05=1.0/(2.0*K), t, factor=alfa/beta*K, lnga1;
if (median) {
for (i=0; i<K; i++) rK[i]=PointGamma((i*2.0+1)*gap05, alfa, beta);
for (i=0,t=0; i<K; i++) t+=rK[i];
for (i=0; i<K; i++) rK[i]*=factor/t;
}
else {
lnga1=LnGamma(alfa+1);
for (i=0; i<K-1; i++)
freqK[i]=PointGamma((i+1.0)/K, alfa, beta);
for (i=0; i<K-1; i++)
freqK[i]=IncompleteGamma(freqK[i]*beta, alfa+1, lnga1);
rK[0] = freqK[0]*factor;
rK[K-1] = (1-freqK[K-2])*factor;
for (i=1; i<K-1; i++) rK[i] = (freqK[i]-freqK[i-1])*factor;
}
for (i=0; i<K; i++) freqK[i]=1.0/K;
return (0);
}
void DGamRateProcess::UpdateDiscreteCategories() {
if (withpinv) {
double* x = new double[GetNcat()-1];
double* y = new double[GetNcat()-1];
double lg = rnd::GetRandom().logGamma(alpha+1.0);
for (int i=0; i<GetNcat()-1; i++) {
x[i] = PointGamma((i+1.0)/(GetNcat()-1),alpha,alpha);
}
for (int i=0; i<GetNcat()-2; i++) {
y[i] = IncompleteGamma(alpha*x[i],alpha+1,lg);
}
y[GetNcat()-2] = 1.0;
rate[0] = 0;
rate[1] = (GetNcat()-1) * y[0];
for (int i=1; i<(GetNcat()-1); i++) {
rate[i+1] = (GetNcat()-1) * (y[i] - y[i-1]);
}
delete[] x;
delete[] y;
}
else {
double* x = new double[GetNcat()];
double* y = new double[GetNcat()];
double lg = rnd::GetRandom().logGamma(alpha+1.0);
for (int i=0; i<GetNcat(); i++) {
x[i] = PointGamma((i+1.0)/GetNcat(),alpha,alpha);
}
for (int i=0; i<GetNcat()-1; i++) {
y[i] = IncompleteGamma(alpha*x[i],alpha+1,lg);
}
y[GetNcat()-1] = 1.0;
rate[0] = GetNcat() * y[0];
for (int i=1; i<GetNcat(); i++) {
rate[i] = GetNcat() * (y[i] - y[i-1]);
}
delete[] x;
delete[] y;
}
}
