package prbnmcn-stats

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Parameters
Signature

prbnmcn-stats
- Stats
  - Binning
  - Combi
  - Emp
    
    Empirical_statistics
    
    Float
    
    Rational
  - Fin
    
    Float
    
    Dist
    
    Rational
    
    Dist
  - Finbij
    
    Make
    
    Elt
    
    S
  - Float_table
  - Gen
    
    Infix
    
    Make
    
    Infix
    
    RNG
    
    Rational
    
    Rational
  - Graph
    
    Dist
    
    Graph_statistics
    
    Tree
    
    Undirected_edge
    
    Vertex_bij
    
    Make
    
    Graph
    
    V
    
    Tree
    
    Undirected_edge
    
    Vertex_bij
  - Int_table
  - Log_space
  - Mh
    
    MH_parameters
    
    Make
    
    X
    
    Make_core_sampling_loop
    
    X
  - Pdfs
  - Specfun
  - Stats_intf
    
    Fin_dist
    
    Gen
    
    Infix
    
    Rational
    
    Graph
    
    V
    
    Stateful_PRNG
  - String_table

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Class type

Generic sampling loop.

Parameters

module X : Basic_structures.Basic_intf.Pp

Signature

val mcmc : 
  verbosity:[ `Silent | `Progress | `Trace ] ->
  initial:X.t ->
  burn_in:int ->
  (X.t -> ('s, X.t) Stats_intf.gen) ->
  ('s, ('s, X.t) Stats_intf.gen) Stats_intf.gen

The sampler function produces a generative probability. More precisely: each sample from mcmc ~verbosity ~initial ~burn_in is a distinct Markov chain, which samples can in-turn be obtained by calling iteratively the closure returned by mcmc. Concretely, the outer `Stats.gen` corresponds to sampling the burn-in while the inner corresponds to sampling from the actual chain.