📄 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. Thefunctions 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 functionsThe probability functions for the Normal or Gaussian distribution aredescribed 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 probabilityfunction @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, inverseThe @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 asymptotesto @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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