Library
Module
Module type
Parameter
Class
Class type
The prbnmcn-stats
statistical library.
Introduction
prbnmcn-stats
(stats
for short) was designed to construct simple probabilistic models and compute basic statistics over empirical data obtained from various experiments.
The core data type is that of a probability distribution. Distributions come under various guises.
- Empirical distributions are the typical outcome of performing a bunch of measurements or experiments, concretely they are nothing more than a collection of data. The empirical mean, empirical variance and quantiles are typical statistics that can be computed on empirical distributions.
- Generative distributions a.k.a. samplers are used when constructing probabilistic models, they are typically used to generate synthetic data.
- Measures are the mathematical representation of a distribution, associating weights to (sets of) data. This is the form we use to compute statistics such as the mean, the variance, etc of a distribution. Typically, we manipulate only finitely supported measures.
stats
provides modules dedicated for each case, and maps between the various forms under which probability distributions appear.
module Stats_intf : sig ... end
Type signatures.
module Fin : sig ... end
Finite measures implemented as finitely supported functions.
module Emp : sig ... end
Empirical distributions.
module Gen : sig ... end
Generative distributions.
module Pdfs : sig ... end
Probability density functions.
module Combi : sig ... end
Simple combinatorics.
module Mh : sig ... end
Metropolis-Hastings MCMC
module Finbij : sig ... end
Bijections between finite sets and {0; ...; n-1}
.
module Graph : sig ... end
Basic statistics on graphs (experimental)
module Log_space : sig ... end
Log-space computation
module Binning : sig ... end
Binning finitely supported distributions
module Specfun : sig ... end
module Int_table : sig ... end
module String_table : sig ... end
module Float_table : sig ... end