...one of the most highly
regarded and expertly designed C++ library projects in the
world.
— Herb Sutter and Andrei
Alexandrescu, C++
Coding Standards
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.
Carlson's algorithms (mainly R_{J}) are somewhat prone to internal overflow/underflow when the arguments are very large or small. The homogeneity relations:
R_{F}(ka, kb, kc) = k^{-1/2} R_{F}(a, b, c)
and
R_{J}(ka, kb, kc, kr) = k^{-3/2} R_{J}(a, b, c, r)
could be used to sidestep trouble here: provided the problem domains can be accurately identified. (Medium Priority).
There is a problem area at arbitrary precision when a is very close to 1. However, note that the value for T(h, 1) is well known and easy to compute, and if we replaced the a^{k} terms in series T1, T2 or T4 by (a^{k} - 1) then we would have the difference between T(h, a) and T(h, 1). Unfortunately this doesn't improve the convergence of those series in that area. It certainly looks as though a new series in terms of (1-a)^{k} is both possible and desirable in this area, but it remains elusive at present.
These are useful in engineering applications - we have had a request to add these.
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:
Distribution |
R |
Mathematica 6 |
NIST |
Regress+ |
Matlab |
---|---|---|---|---|---|
Geometric |
X |
X |
- |
- |
X |
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 |
Log Logistic |
- |
- |
- |
- |
X |
Tukey (Studentized range) |
X |
- |
- |
- |
- |
Wilcoxon rank sum |
X |
- |
- |
- |
- |
Wincoxon signed rank |
X |
- |
- |
- |
- |
Non-central Beta |
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 |
- |
Kolmogorov Distribution |
- |
- |
- |
- |
- |
Also asked for more than once: