|dstats.alloc||Stuff having to do with memory management. Mostly a copy of RegionAllocator
for now until it gets into Phobos, as well as some RegionAllocator-specific
|dstats.base||Relatively low-level primitives on which to build higher-level math/stat
functionality. Some are used internally, some are just things that may be
useful to users of this library. This module is starting to take on the
appearance of a small utility library.
|dstats.cor||Pearson, Spearman and Kendall correlations, covariance.
|dstats.distrib||Probability distribution CDFs, PDFs/PMFs, and a few inverse CDFs.
|dstats.infotheory||Basic information theory. Joint entropy, mutual information, conditional
mutual information. This module uses the base 2 definition of these
quantities, i.e, entropy, mutual info, etc. are output in bits.
|dstats.kerneldensity||This module contains a small but growing library for performing kernel
|dstats.pca||This module contains a basic implementation of principal component analysis,
based on the NIPALS algorithm. This is fast when you only need the first
few components (which is usually the case since PCA's main uses are
visualization and dimensionality reduction). However, convergence slows
drastically after the first few components have been removed and most of
the matrix is just noise.
|dstats.random||Generates random samples from a various probability distributions.
These are mostly D ports of the NumPy random number generators.
|dstats.regress||A module for performing linear regression. This module has an unusual
interface, as it is range-based instead of matrix based. Values for
independent variables are provided as either a tuple or a range of ranges.
This means that one can use, for example, map, to fit high order models and
lazily evaluate certain values. (For details, see examples below.)
|dstats.sort||A comprehensive sorting library for statistical functions. Each function
takes N arguments, which are arrays or array-like objects, sorts the first
and sorts the rest in lockstep. For merge and insertion sort, if the last
argument is a ulong*, increments the dereference of this ulong* by the bubble
sort distance between the first argument and the sorted version of the first
argument. This is useful for some statistical calculations.
|dstats.summary||Summary statistics such as mean, median, sum, variance, skewness, kurtosis.
Except for median and median absolute deviation, which cannot be calculated
online, all summary statistics have both an input range interface and an
output range interface.
|dstats.tests||Hypothesis testing beyond simple CDFs. All functions work with input
ranges with elements implicitly convertible to double unless otherwise noted.
|dstats||Convenience module that simply publicly imports everything else.