コード例 #1
0
ファイル: SNCP.cpp プロジェクト: kujta1/rjmcmc-1
double sncp_model::calculate_normalising_constant(double alpha,double z,double bound){
  long double norm =1 ; 
  if(bound>0){
   norm = gsl_cdf_gamma_P(bound,alpha,1.0/(double)z);
  }
  return norm;
}
コード例 #2
0
void Model::set_custom_prob(double alpha, double scale) {
    custom_prob.resize(0);
    bool stop = false;
    double w = 0.0;
    while ((!stop)&(custom_prob.size()<400)) {
        w = gsl_cdf_gamma_P(custom_prob.size(), alpha, scale);
        custom_prob.push_back(w);
        stop = w > 0.99999;
    }
    for (int i=1; i!=custom_prob.size(); ++i) custom_prob[i-1] = custom_prob[i]-custom_prob[i-1];
    custom_prob.pop_back();
}
コード例 #3
0
ファイル: gsl_cdf__poisson.c プロジェクト: DsRQuicke/praat
double
gsl_cdf_poisson_Q (const unsigned int k, const double mu)
{
  double Q;
  double a;

  if (mu <= 0.0)
    {
      CDF_ERROR ("mu <= 0", GSL_EDOM);
    }

  a = (double) k + 1.0;
  Q = gsl_cdf_gamma_P (mu, a, 1.0);

  return Q;
}
コード例 #4
0
ファイル: gammainv.c プロジェクト: Ayato-Harashima/CMVS-PMVS
double
gsl_cdf_gamma_Pinv (const double P, const double a, const double b)
{
  double x;

  if (P == 1.0)
    {
      return GSL_POSINF;
    }
  else if (P == 0.0)
    {
      return 0.0;
    }

  /* Consider, small, large and intermediate cases separately.  The
     boundaries at 0.05 and 0.95 have not been optimised, but seem ok
     for an initial approximation.

     BJG: These approximations aren't really valid, the relevant
     criterion is P*gamma(a+1) < 1. Need to rework these routines and
     use a single bisection style solver for all the inverse
     functions.
  */

  if (P < 0.05)
    {
      double x0 = exp ((gsl_sf_lngamma (a) + log (P)) / a);
      x = x0;
    }
  else if (P > 0.95)
    {
      double x0 = -log1p (-P) + gsl_sf_lngamma (a);
      x = x0;
    }
  else
    {
      double xg = gsl_cdf_ugaussian_Pinv (P);
      double x0 = (xg < -0.5*sqrt (a)) ? a : sqrt (a) * xg + a;
      x = x0;
    }

  /* Use Lagrange's interpolation for E(x)/phi(x0) to work backwards
     to an improved value of x (Abramowitz & Stegun, 3.6.6) 

     where E(x)=P-integ(phi(u),u,x0,x) and phi(u) is the pdf.
   */

  {
    double lambda, dP, phi;
    unsigned int n = 0;

  start:
    dP = P - gsl_cdf_gamma_P (x, a, 1.0);
    phi = gsl_ran_gamma_pdf (x, a, 1.0);

    if (dP == 0.0 || n++ > 32)
      goto end;

    lambda = dP / GSL_MAX (2 * fabs (dP / x), phi);

    {
      double step0 = lambda;
      double step1 = -((a - 1) / x - 1) * lambda * lambda / 4.0;

      double step = step0;
      if (fabs (step1) < 0.5 * fabs (step0))
        step += step1;

      if (x + step > 0)
        x += step;
      else
        {
          x /= 2.0;
        }

      if (fabs (step0) > 1e-10 * x || fabs(step0 * phi) > 1e-10 * P)
        goto start;
    }

  end:
    if (fabs(dP) > GSL_SQRT_DBL_EPSILON * P)
      {
        GSL_ERROR_VAL("inverse failed to converge", GSL_EFAILED, GSL_NAN);
      }
    
    return b * x;
  }
}
コード例 #5
0
ファイル: rgamma_test.cpp プロジェクト: reedacartwright/wrs
double rgamma_inv(void) {
	double x = rand_gamma(rng,100,1.0);
	return gsl_cdf_gamma_P(x,100,1.0);
}
コード例 #6
0
ファイル: chisq.c プロジェクト: lemahdi/mglib
double
gsl_cdf_chisq_P (const double x, const double nu)
{
  return gsl_cdf_gamma_P (x, nu / 2, 2.0);
}
コード例 #7
0
ファイル: gammainv.c プロジェクト: CNMAT/CNMAT-Externs
double
gsl_cdf_gamma_Pinv (const double P, const double a, const double b)
{
  double x;

  if (P == 1.0)
    {
      return GSL_POSINF;
    }
  else if (P == 0.0)
    {
      return 0.0;
    }

  /* Consider, small, large and intermediate cases separately.  The
     boundaries at 0.05 and 0.95 have not been optimised, but seem ok
     for an initial approximation. */

  if (P < 0.05)
    {
      double x0 = exp ((gsl_sf_lngamma (a) + log (P)) / a);
      x = x0;
    }
  else if (P > 0.95)
    {
      double x0 = -log1p (-P) + gsl_sf_lngamma (a);
      x = x0;
    }
  else
    {
      double xg = gsl_cdf_ugaussian_Pinv (P);
      double x0 = (xg < -sqrt (a)) ? a : sqrt (a) * xg + a;
      x = x0;
    }

  /* Use Lagrange's interpolation for E(x)/phi(x0) to work backwards
     to an improved value of x (Abramowitz & Stegun, 3.6.6) 

     where E(x)=P-integ(phi(u),u,x0,x) and phi(u) is the pdf.
   */

  {
    double lambda, dP, phi;
    unsigned int n = 0;

  start:
    dP = P - gsl_cdf_gamma_P (x, a, 1.0);
    phi = gsl_ran_gamma_pdf (x, a, 1.0);

    if (dP == 0.0 || n++ > 32)
      goto end;

    lambda = dP / GSL_MAX (2 * fabs (dP / x), phi);

    {
      double step0 = lambda;
      double step1 = -((a - 1) / x - 1) * lambda * lambda / 4.0;

      double step = step0;
      if (fabs (step1) < fabs (step0))
        step += step1;

      if (x + step > 0)
        x += step;
      else
        {
          x /= 2.0;
        }

      if (fabs (step0) > 1e-10 * x)
        goto start;
    }

  }

end:
  return b * x;
}