📄 erf_inv.qbk
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[section:error_inv Error Function Inverses][h4 Synopsis]``#include <boost/math/special_functions/erf.hpp>`` namespace boost{ namespace math{ template <class T> ``__sf_result`` erf_inv(T p); template <class T, class ``__Policy``> ``__sf_result`` erf_inv(T p, const ``__Policy``&); template <class T> ``__sf_result`` erfc_inv(T p); template <class T, class ``__Policy``> ``__sf_result`` erfc_inv(T p, const ``__Policy``&); }} // namespaces The return type of these functions is computed using the __arg_pomotion_rules:the return type is `double` if T is an integer type, and T otherwise.[optional_policy][h4 Description] template <class T> ``__sf_result`` erf_inv(T z); template <class T, class ``__Policy``> ``__sf_result`` erf_inv(T z, const ``__Policy``&); Returns the [@http://functions.wolfram.com/GammaBetaErf/InverseErf/ inverse error function]of z, that is a value x such that: p = erf(x);[graph erf_inv] template <class T> ``__sf_result`` erfc_inv(T z); template <class T, class ``__Policy``> ``__sf_result`` erfc_inv(T z, const ``__Policy``&); Returns the inverse of the complement of the error function of z, that is avalue x such that: p = erfc(x);[graph erfc_inv][h4 Accuracy]For types up to and including 80-bit long doubles the approximations usedare accurate to less than ~ 2 epsilon. For higher precision types these functions have the same accuracy as the [link math_toolkit.special.sf_erf.error_function forward error functions].[h4 Testing]There are two sets of tests: * Basic sanity checks attempt to "round-trip" from/x/ to /p/ and back again. These tests have quitegenerous tolerances: in general both the error functions and theirinverses change so rapidly in some places that round tripping to more than a coupleof significant digits isn't possible. This is especially true when/p/ is very near one: in this case there isn't enough "information content" in the input to the inverse function to getback where you started.* Accuracy checks using high-precision test values. These measurethe accuracy of the result, given /exact/ input values.[h4 Implementation]These functions use a rational approximation [jm_rationals] to calculate an initialapproximation to the result that is accurate to ~10[super -19], then only if that has insufficient accuracy compared to the epsilon for T,do we clean up the result using[@http://en.wikipedia.org/wiki/Simple_rational_approximation Halley iteration].Constructing rational approximations to the erf/erfc functions is actuallysurprisingly hard, especially at high precision. For this reason no attempthas been made to achieve 10[super -34 ] accuracy suitable for use with 128-bitreals.In the following discussion, /p/ is the value passed to erf_inv, and /q/ isthe value passed to erfc_inv, so that /p = 1 - q/ and /q = 1 - p/ and in bothcases we want to solve for the same result /x/.For /p < 0.5/ the inverse erf function is reasonably smooth and the approximation: x = p(p + 10)(Y + R(p)) Gives a good result for a constant Y, and R(p) optimised for low absolute errorcompared to |Y|.For q < 0.5 things get trickier, over the interval /0.5 > q > 0.25/the following approximation works well: x = sqrt(-2log(q)) / (Y + R(q)) While for q < 0.25, let z = sqrt(-log(q))Then the result is given by: x = z(Y + R(z - B))As before Y is a constant and the rational function R is optimised for lowabsolute error compared to |Y|. B is also a constant: it is the smallest valueof /z/ for which each approximation is valid. There are several approximationsof this form each of which reaches a little further into the tail of the erfc function (at `long double` precision the extended exponent range compared to`double` means that the tail goes on for a very long way indeed).[endsect][/ :error_inv The Error Function Inverses][/ Copyright 2006 John Maddock and Paul A. Bristow. Distributed under the Boost Software License, Version 1.0. (See accompanying file LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt).]
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