double
librandom::GammaRandomDev::unscaled_gamma( RngPtr r ) const
{
// algorithm depends on order a
if ( a == 1 )
return -std::log( r->drandpos() );
else if ( a < 1 )
{
// Johnk's rejection algorithm, see [1], p. 418
double X;
double Y;
double S;
do
{
X = std::pow( r->drand(), ju );
Y = std::pow( r->drand(), jv );
S = X + Y;
} while ( S > 1 );
if ( X > 0 )
return -std::log( r->drandpos() ) * X / S;
else
return 0;
}
else
{
// Best's rejection algorithm, see [1], p. 410
bool accept = false;
double X = 0.0;
do
{
const double U = r->drand();
if ( U == 0 || U == 1 )
continue; // accept guaranteed false
const double V = r->drand();
const double W = U * ( 1 - U ); // != 0
const double Y = std::sqrt( bc / W ) * ( U - 0.5 );
X = bb + Y;
if ( X > 0 )
{
const double Z = 64 * W * W * W * V * V;
accept = Z <= 1 - 2 * Y * Y / X;
if ( !accept )
accept = std::log( Z ) <= 2 * ( bb * std::log( X / bb ) - Y );
}
} while ( !accept );
return X;
}
}
double librandom::NormalRandomDev::operator()( RngPtr r ) const
{
// Box-Muller algorithm, see Knuth TAOCP, vol 2, 3rd ed, p 122
// we waste one number
double V1;
double V2;
double S;
do
{
V1 = 2 * r->drand() - 1;
V2 = 2 * r->drand() - 1;
S = V1 * V1 + V2 * V2;
} while ( S >= 1 );
if ( S != 0 )
S = V1 * std::sqrt( -2 * std::log( S ) / S );
return mu_ + sigma_ * S;
}
double librandom::LognormalRandomDev::operator()( RngPtr r ) const
{
// We could forward here to a NormalRandomDev, but that would
// require keeping such an object. Given that the Box-Muller code
// is short, we just duplicate it here.
// Box-Muller algorithm, see Knuth TAOCP, vol 2, 3rd ed, p 122
// we waste one number
double V1;
double V2;
double S;
do
{
V1 = 2 * r->drand() - 1;
V2 = 2 * r->drand() - 1;
S = V1 * V1 + V2 * V2;
} while ( S >= 1 );
if ( S != 0 )
S = V1 * std::sqrt( -2 * std::log( S ) / S );
return std::exp( mu_ + sigma_ * S );
}
