/**
* Returns the regularized gamma function Q(a, x) = 1 - P(a, x).
*/
public static function regularizedGammaQ($a, $x, $epsilon, $maxIterations)
{
if (is_nan($a) || is_nan($x) || $a <= 0.0 || $x < 0.0) {
$ret = NAN;
} else {
if ($x == 0.0) {
$ret = 1.0;
} else {
if ($x < $a + 1.0) {
// use regularizedGammaP because it should converge faster in this
// case.
$ret = 1.0 - Statistics::regularizedGammaP($a, $x, $epsilon, $maxIterations);
} else {
$ret = 1.0 / Statistics::cfEvaluate($a, $x, $epsilon, $maxIterations);
$ret = exp(-$x + $a * log($x) - Statistics::logGamma($a)) * $ret;
}
}
}
return $ret;
}
notify('InvGamma1pm1', 0.12837916709551, Statistics::invGamma1pm1(0.5));
try {
Statistics::invGamma1pm1(-2.5);
notify('InvGamma1pm1 too small', "Exception thrown", "Ok");
} catch (Exception $ex1) {
notify('InvGamma1pm1 too small', $ex1, $ex1);
}
try {
Statistics::invGamma1pm1(2.5);
notify('InvGamma1pm1 too large', "Exception thrown", "Ok");
} catch (Exception $ex1) {
notify('InvGamma1pm1 too large', $ex1, $ex1);
}
notify('Lanczos', 19.194552097849, Statistics::lanczos(0.5));
notify('LogGamma', 0.5723649429247, Statistics::logGamma(0.5));
notify('RegularizedGammaP', 0.77932863808015, Statistics::regularizedGammaP(0.5, 0.75, 1.0E-15, 10000));
notify('RegularizedGammaQ', 0.061368829139402, Statistics::regularizedGammaQ(0.5, 1.75, 1.0E-15, 10000));
// Global test
$rtgm->calculate();
notify('Get risk coefficient', $riskCoeff, $rtgm->riskCoeff);
notify('Get rtgm iter', $rtgmIters, $rtgm->rtgmIters);
notify('Get risk iter', $riskIters, $rtgm->riskIters);
printf("\nriskCoeff: %s\n", $rtgm->riskCoeff);
printf("rtgmIters: [%s]\n", implode(', ', $rtgm->rtgmIters));
printf("riskIters: [%s]\n", implode(', ', $rtgm->riskIters));
} catch (Exception $e) {
print $e->getMessage() . "\n";
}
exit($exit_code);
?>