ceph/src/boost/libs/math/doc/overview/credits.qbk

   1 [section:credits Credits and Acknowledgements]
   2
   3 Hubert Holin started the Boost.Math library.  The
   4 Quaternions, Octonions, inverse
   5 hyperbolic functions, and the sinus cardinal functions are his.
   6
   7 Daryle Walker wrote the integer gcd and lcm functions.
   8
   9 John Maddock started the special functions, the beta, gamma, erf, polynomial,
  10 and factorial functions are his, as is the "Toolkit" section, and many
  11 of the statistical distributions.
  12
  13 Paul A. Bristow threw down the challenge in
  14 [@http://www2.open-std.org/JTC1/SC22/WG21/docs/papers/2004/n1668.pdf
  15 A Proposal to add Mathematical Functions for Statistics to the C++
  16 Standard Library] to add the key math functions, especially those essential for
  17 statistics. After JM accepted and solved the difficult problems,
  18 not only numerically, but in full C++ template style, PAB
  19 implemented a few of the statistical distributions. PAB also tirelessly
  20 proof-read everything that JM threw at him (so that all
  21 remaining editorial mistakes are his fault).
  22
  23 Xiaogang Zhang worked on the Bessel functions and elliptic integrals for his
  24 Google Summer of Code project 2006.
  25
  26 Bruno Lalande submitted the "compile time power of a runtime base" code.
  27
  28 Johan R'''&#xE5;'''de wrote the optimised floating-point classification
  29 and manipulation code, and nonfinite facets to permit C99 output of infinities and NaNs.
  30 (nonfinite facets were not added until Boost 1.47 but had been in use with Boost.Spirit).
  31 This library was based on a suggestion from Robert Ramey, author of Boost.Serialization.
  32 Paul A. Bristow expressed the need for better handling of
  33 [@http://www.open-std.org/jtc1/sc22/wg21/docs/papers/2006/n2022.pdf
  34 Input & Output of NaN and infinity for the C++ Standard Library]
  35 and suggested following the C99 format.
  36
  37 Antony Polukhin improved lexical cast avoiding stringstream so that
  38 it was no longer necessary to use a globale C99 facet to handle nonfinites.
  39
  40 H'''&#xE5;'''kan Ard'''&#xF6;''',
  41 Boris Gubenko, John Maddock,
  42 Markus Sch'''&#xF6;'''pflin
  43 and Olivier Verdier tested the floating-point library and
  44 Martin Bonner, Peter Dimov and John Maddock provided valuable advice.
  45
  46 Gautam Sewani coded the logistic distribution as part of a Google Summer of Code project 2008.
  47
  48 M. A. (Thijs) van den Berg coded the Laplace distribution.
  49 (Thijs has also threatened to implement some multivariate distributions).
  50
  51 Thomas Mang requested the inverse gamma in chi squared distributions
  52 for Bayesian applications and helped in their implementation,
  53 and provided a nice example of their use.
  54
  55 Professor Nico Temme for advice on the inverse incomplete beta function.
  56
  57 [@http://www.shoup.net Victor Shoup for NTL],
  58 without which it would have much more difficult to
  59 produce high accuracy constants, and especially
  60 the tables of accurate values for testing.
  61
  62 We are grateful to Joel Guzman for helping us stress-test his
  63 [@http://www.boost.org/tools/quickbook/index.htm Boost.Quickbook]
  64 program used to generate the html and pdf versions
  65 of this document, adding several new features en route.
  66
  67 Plots of the functions and distributions were prepared in
  68 [@http://www.w3.org/ W3C] standard
  69 [@http://www.svg.org/ Scalable Vector Graphic (SVG)] format
  70 using a program created by Jacob Voytko during a
  71 [@http://code.google.com/soc/2007/ Google Summer of Code (2007)].
  72 From 2012, the latest versions of all Internet Browsers have support
  73 for rendering SVG (with varying quality).  Older versions, especially
  74 (Microsoft Internet Explorer (before IE 9) lack native SVG support
  75 but can be made to work with
  76 [@http://www.adobe.com/svg/viewer/install/ Adobe's free SVG viewer] plugin).
  77 The SVG files can be converted to JPEG or PNG using
  78 [@http://www.inkscape.org/ Inkscape].
  79
  80 We are also indebted to Matthias Schabel for managing the formal Boost-review
  81 of this library, and to all the reviewers - including Guillaume Melquiond,
  82 Arnaldur Gylfason, John Phillips, Stephan Tolksdorf and Jeff Garland
  83 - for their many helpful comments.
  84
  85 Thanks to Mark Coleman and Georgi Boshnakov for spot test values
  86 from __Mathematica, and of course,
  87 to Eric Weisstein for nurturing __Mathworld, an invaluable resource.
  88
  89 The Skew-normal distribution and Owen's t function were written by Benjamin Sobotta.
  90
  91 We thank Thomas Mang for persuading us to allow t distributions
  92 to have infinite degrees of freedom
  93 and contributing to some long discussions about how to improve accuracy
  94 for large non-centrality and/or large degrees of freedom.
  95
  96 Christopher Kormanyos wrote the e_float multiprecision library __TOMS910
  97 which formed the basis for the Boost.Multiprecision library
  98 which now can be used to allow most functions and distributions
  99 to be computed up to a precision of the users' choice,
 100 no longer restricted to built-in floating-point types like double.
 101 (And thanks to Topher Cooper for bring Christopher's e_float to our attention).
 102
 103 Christopher Kormanyos wrote some examples for using __multiprecision,
 104 and added methods for finding zeros of Bessel Functions.
 105
 106 Marco Guazzone provided the hyper-geometric distribution.
 107
 108 Rocco Romeo has found numerous small bugs and generally stress tested the
 109 special functions code to near destruction!
 110
 111 Jeremy William Murphy added polynomial arithmetic tools.
 112
 113 Thomas Luu provided improvements to the quantile of the non-central chi squared distribution quantile.
 114 and his thesis
 115 * [@http://discovery.ucl.ac.uk/1482128/ Fast and accurate parallel computation of quantile functions for random number generation, 2016].
 116
 117 and his paper
 118
 119 Luu, Thomas; (2015), Efficient and Accurate Parallel Inversion of the Gamma Distribution,
 120 SIAM Journal on Scientific Computing , 37 (1) C122 - C141,
 121 [@http://dx.doi.org/10.1137/14095875X].
 122
 123 These also promise to help improve algorithms for computation of  quantile of several disitributions,
 124 especially for parallel computation using GPUs.
 125
 126 [endsect] [/section:credits Credits and Acknowledgements]
 127
 128 [/
 129   Copyright 2006, 2007, 2008, 2009, 2010, 2012, 2013, 2015, 2016 John Maddock and Paul A. Bristow.
 130   Distributed under the Boost Software License, Version 1.0.
 131   (See accompanying file LICENSE_1_0.txt or copy at
 132   http://www.boost.org/LICENSE_1_0.txt).
 133 ]
 134