Error Functions

The error function is described in Abramowitz & Stegun, Chapter 7.

gsl_sf_erf(x)

This routine computes the error function \(\operatorname{erf}(x)\), where

\[\operatorname{erf}(x) = (2/\sqrt{\pi}) \int_0^x \exp(-t^2) dt.\]
gsl_sf_erfc(x)

This routine computes the complementary error function

\[\operatorname{erfc}(x) = 1 - \operatorname{erf}(x) = (2/\sqrt{\pi}) \int_x^\infty \exp(-t^2) dt.\]
gsl_sf_log_erfc(x)

This routine computes the logarithm of the complementary error function \(\log(\operatorname{erfc}(x))\).

Probability functions

The probability functions for the Normal or Gaussian distribution are described in Abramowitz & Stegun, Section 26.2.

gsl_sf_erf_Z(x)

This routine computes the Gaussian probability density function \(Z(x) = (1/\sqrt{2\pi}) \exp(-x^2/2)\).

gsl_sf_erf_Q(x)

This routine computes the upper tail of the Gaussian probability function \(Q(x) = (1/\sqrt{2\pi}) \int_x^\infty \exp(-t^2/2) dt\).

The hazard function for the normal distribution, also known as the inverse Mills’ ratio, is defined as,

\[h(x) = Z(x)/Q(x) = \sqrt{2/\pi} \exp(-x^2 / 2) / \operatorname{erfc}(x/\sqrt 2)\]

It decreases rapidly as \(x\) approaches \(-\infty\) and asymptotes to \(h(x) \sim x\) as \(x\) approaches \(+\infty\).

gsl_sf_hazard(x)

This routine computes the hazard function for the normal distribution.