bump version to 12.2.2-pve1

[ceph.git] / ceph / src / boost / libs / math / doc / sf / erf_inv.qbk

[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_promotion_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 a
value x such that:

   p = erfc(x);

[graph erfc_inv]

[h4 Accuracy]

For types up to and including 80-bit long doubles the approximations used
are accurate to less than ~ 2 epsilon.  For higher precision types these 
functions have the same accuracy as the 
[link math_toolkit.sf_erf.error_function forward error functions].

[table_erf_inv]

[table_erfc_inv]

[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 quite
generous tolerances: in general both the error functions and their
inverses change so rapidly in some places that round tripping to more than a couple
of 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 get
back where you started.
* Accuracy checks using high-precision test values.  These measure
the accuracy of the result, given /exact/ input values.

[h4 Implementation]

These functions use a rational approximation [jm_rationals] 
to calculate an initial
approximation 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 actually
surprisingly hard, especially at high precision.  For this reason no attempt
has been made to achieve 10[super -34 ] accuracy suitable for use with 128-bit
reals.

In the following discussion, /p/ is the value passed to erf_inv, and /q/ is
the value passed to erfc_inv, so that /p = 1 - q/ and /q = 1 - p/ and in both
cases 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 error
compared 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 low
absolute error compared to |Y|.  B is also a constant: it is the smallest value
of /z/ for which each approximation is valid.  There are several approximations
of 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).
]