| [section:issues Known Issues, and Todo List] |
| |
| This section lists those issues that are known about. |
| |
| Predominantly this is a TODO list, or a list of possible |
| future enhancements. Items labled "High Priority" effect |
| the proper functioning of the component, and should be fixed |
| as soon as possible. Items labled "Medium Priority" are |
| desirable enhancements, often pertaining to the performance |
| of the component, but do not effect it's accuracy or functionality. |
| Items labled "Low Priority" should probably be investigated at |
| some point. Such classifications are obviously highly subjective. |
| |
| If you don't see a component listed here, then we don't have any known |
| issues with it. |
| |
| [h4 tgamma] |
| |
| * Can the __lanczos be optimized any further? (low priority) |
| |
| [h4 Incomplete Beta] |
| |
| * Investigate Didonato and Morris' asymptotic expansion for large a and b |
| (medium priority). |
| |
| [h4 Inverse Gamma] |
| |
| * Investigate whether we can skip iteration altogether if the first approximation |
| is good enough (Medium Priority). |
| |
| [h4 Polynomials] |
| |
| * The Legendre and Laguerre Polynomials have surprisingly different error |
| rates on different platforms, considering they are evaluated with only |
| basic arithmetic operations. Maybe this is telling us something, or maybe not |
| (Low Priority). |
| |
| [h4 Elliptic Integrals] |
| |
| * Carlson's algorithms are essentially unchanged from Xiaogang Zhang's |
| Google Summer of Code student project, and are based on Carlson's |
| original papers. However, Carlson has revised his algorithms since then |
| (refer to the references in the elliptic integral docs for a list), to |
| improve performance and accuracy, we may be able to take advantage |
| of these improvements too (Low Priority). |
| * [para Carlson's algorithms (mainly R[sub J]) are somewhat prone to |
| internal overflow/underflow when the arguments are very large or small. |
| The homogeneity relations:] |
| [para R[sub F](ka, kb, kc) = k[super -1/2] R[sub F](a, b, c)] |
| [para and] |
| [para R[sub J](ka, kb, kc, kr) = k[super -3/2] R[sub J](a, b, c, r)] |
| [para could be used to sidestep trouble here: provided the problem domains |
| can be accurately identified. (Medium Priority).] |
| * Carlson's R[sub C] can be reduced to elementary funtions (asin and log), |
| would it be more efficient evaluated this way, rather than by Carlson's |
| algorithms? (Low Priority). |
| * Should we add an implementation of Carlson's R[sub G]? It's not |
| required for the Legendre form integrals, but some people may find it |
| useful (Low Priority). |
| * There are a several other integrals: D([phi], k), Z([beta], k), |
| [Lambda][sub 0]([beta], k) and Bulirsch's ['el] functions that could |
| be implemented using Carlson's integrals (Low Priority). |
| * The integrals K(k) and E(k) could be implemented using rational |
| approximations (both for efficiency and accuracy), |
| assuming we can find them. (Medium Priority). |
| * There is a sub-domain of __ellint_3 that is unimplemented (see the docs |
| for details), currently |
| it's not clear how to solve this issue, or if it's ever likely |
| to be an real problem in practice - especially as most other implementations |
| don't support this domain either (Medium Priority). |
| |
| [h4 Inverse Hyperbolic Functions] |
| |
| * These functions are inherited from previous Boost versions, |
| before __log1p became widely available. Would they be better expressed |
| in terms of this function? This is probably only an issue |
| for very high precision types (Low Priority). |
| |
| [h4 Statistical distributions] |
| |
| * Student's t Perhaps switch to normal distribution as a better approximation for very large degrees of freedom? |
| |
| [h4 Feature Requests] |
| |
| The following table lists distributions that are found in other packages |
| but which are not yet present here, the more frequently the distribution |
| is found, the higher the priority for implementing it: |
| |
| [table |
| [[Distribution][R][Mathematica 6][NIST][Regress+][Matlab]] |
| |
| [/3 votes:] |
| [[Inverse Gausian / Inverse Normal][-][X][-][X][X]] |
| [[Geometric][X][X][-][-][X]] |
| |
| [/2 votes:] |
| [[Multinomial][X][-][-][-][X]] |
| [[Tukey Lambda][X][-][X][-][-]] |
| [[Half Normal / Folded Normal][-][X][-][X][-]] |
| [[Chi][-][X][-][X][-]] |
| [[Gumbel][-][X][-][X][-]] |
| [[Discrete Uniform][-][X][-][-][X]] |
| [[Log Series][-][X][-][X][-]] |
| [[Nakagami (generalised Chi)][-][-][-][X][X]] |
| |
| [/1 vote:] |
| [[Log Logistic][-][-][-][-][X]] |
| [[Tukey (Studentized range)][X][-][-][-][-]] |
| [[Wilcoxon rank sum][X][-][-][-][-]] |
| [[Wincoxon signed rank][X][-][-][-][-]] |
| [[Non-central Beta][X][-][-][-][-]] |
| [[Laplace][-][X][-][-][-]] |
| [[Maxwell][-][X][-][-][-]] |
| [[Beta-Binomial][-][X][-][-][-]] |
| [[Beta-negative Binomial][-][X][-][-][-]] |
| [[Zipf][-][X][-][-][-]] |
| [[Birnbaum-Saunders / Fatigue Life][-][-][X][-][-]] |
| [[Double Exponential][-][-][X][-][-]] |
| [[Power Normal][-][-][X][-][-]] |
| [[Power Lognormal][-][-][X][-][-]] |
| [[Cosine][-][-][-][X][-]] |
| [[Double Gamma][-][-][-][X][-]] |
| [[Double Weibul][-][-][-][X][-]] |
| [[Hyperbolic Secant][-][-][-][X][-]] |
| [[Semicircular][-][-][-][X][-]] |
| [[Bradford][-][-][-][X][-]] |
| [[Birr / Fisk][-][-][-][X][-]] |
| [[Reciprocal][-][-][-][X][-]] |
| ] |
| |
| Also asked for more than once: |
| |
| * Add support for interpolated distributions, possibly combine with numeric |
| integration and differentiation. |
| * Add support for bivariate and multivariate distributions: most especially the normal. |
| * Add support for the log of the cdf and pdf: this is mainly a performance optimisation since we can avoid |
| some special function calls for some distributions by returning the log of the result. |
| |
| [endsect][/section:issues Known Issues, and Todo List] |
| |
| [/ |
| 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). |
| ] |