📄 specfunc-erf.texi
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@cindex error function
@cindex erf(x)
@cindex erfc(x)
The error function is described in Abramowitz & Stegun, Chapter 7. The
functions in this section are declared in the header file
@file{gsl_sf_erf.h}.
@menu
* Error Function::
* Complementary Error Function::
* Log Complementary Error Function::
* Probability functions::
@end menu
@node Error Function
@subsection Error Function
@deftypefun double gsl_sf_erf (double @var{x})
@deftypefunx int gsl_sf_erf_e (double @var{x}, gsl_sf_result * @var{result})
These routines compute the error function
@c{$\erf(x) = (2/\sqrt{\pi}) \int_0^x dt \exp(-t^2)$}
@math{erf(x) = (2/\sqrt(\pi)) \int_0^x dt \exp(-t^2)}.
@comment Exceptional Return Values: none
@end deftypefun
@node Complementary Error Function
@subsection Complementary Error Function
@deftypefun double gsl_sf_erfc (double @var{x})
@deftypefunx int gsl_sf_erfc_e (double @var{x}, gsl_sf_result * @var{result})
These routines compute the complementary error function
@c{$\erfc(x) = 1 - \erf(x) = (2/\sqrt{\pi}) \int_x^\infty \exp(-t^2)$}
@math{erfc(x) = 1 - erf(x) = (2/\sqrt(\pi)) \int_x^\infty \exp(-t^2)}.
@comment Exceptional Return Values: none
@end deftypefun
@node Log Complementary Error Function
@subsection Log Complementary Error Function
@deftypefun double gsl_sf_log_erfc (double @var{x})
@deftypefunx int gsl_sf_log_erfc_e (double @var{x}, gsl_sf_result * @var{result})
These routines compute the logarithm of the complementary error function
@math{\log(\erfc(x))}.
@comment Exceptional Return Values: none
@end deftypefun
@node Probability functions
@subsection Probability functions
The probability functions for the Normal or Gaussian distribution are
described in Abramowitz & Stegun, Section 26.2.
@deftypefun double gsl_sf_erf_Z (double @var{x})
@deftypefunx int gsl_sf_erf_Z_e (double @var{x}, gsl_sf_result * @var{result})
These routines compute the Gaussian probability function @math{Z(x) =
(1/(2\pi)) \exp(-x^2/2)}.
@end deftypefun
@deftypefun double gsl_sf_erf_Q (double @var{x})
@deftypefunx int gsl_sf_erf_Q_e (double @var{x}, gsl_sf_result * @var{result})
These routines compute the upper tail of the Gaussian probability
function @math{Q(x) = (1/(2\pi)) \int_x^\infty dt \exp(-t^2/2)}.
@comment Exceptional Return Values: none
@end deftypefun
@cindex hazard function, normal distribution
@cindex Mill's ratio, inverse
The @dfn{hazard function} for the normal distrbution,
also known as the inverse Mill's ratio, is defined as
@math{h(x) = Z(x)/Q(x) = \sqrt{2/\pi} \exp(-x^2 / 2) / \erfc(x/\sqrt 2)}.
It decreases rapidly as @math{x} approaches @math{-\infty} and asymptotes
to @math{h(x) \sim x} as @math{x} approaches @math{+\infty}.
@deftypefun double gsl_sf_hazard (double @var{x})
@deftypefunx int gsl_sf_hazard_e (double @var{x}, gsl_sf_result * @var{result})
These routines compute the hazard function for the normal distribution.
@comment Exceptional Return Values: GSL_EUNDRFLW
@end deftypefun
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