package prbnmcn-stats

You can search for identifiers within the package.

in-package search v0.2.0

prbnmcn-stats
- Stats
  - Binning
  - Combi
  - Emp
    
    Empirical_statistics
    
    Float
    
    Rational
  - Fin
    
    Float
    
    Dist
    
    Rational
    
    Dist
  - Finbij
    
    Make
    
    Elt
    
    S
  - Gen
    
    Infix
    
    Rational
  - Graph
    
    Dist
    
    Graph_statistics
    
    Table
    
    Undirected_edge
    
    Vertex_bij
    
    Make
    
    Graph
    
    V
    
    Table
    
    Undirected_edge
    
    Vertex_bij
  - Log_space
  - Mh
    
    MH_parameters
    
    Make
    
    X
    
    Make_core_sampling_loop
    
    X
  - Pdfs
  - Stats_intf
    
    Fin_dist
    
    Fin_fun
    
    V
    
    Basis
    
    R
    
    Fin_kernel
    
    V
    
    Basis
    
    R
    
    Gen
    
    Infix
    
    Rational
    
    Graph
    
    V
    
    Sampling_monad
    
    Infix

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Module
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Parameter
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Class type

Generative distributions.

include Stats_intf.Gen

type parameters = {

nsamples : int;
state : Random.State.t;

}

include Stats_intf.Sampling_monad
  with type 'a res =
         parameters ->
         (module Basic_structures.Basic_intf.Std with type t = 'a) ->
         ('a, float) Stats_intf.fin_mes

type 'a t = 'a Stats_intf.gen

'a t is the type of computations of type 'a

type 'a res =
  parameters ->
  (module Basic_structures.Basic_intf.Std with type t = 'a) ->
  ('a, float) Stats_intf.fin_mes

'a res is the outcome of running a computation of type 'a

val return : 'a -> 'a t

return x injects a value x as a computation

val bind : 'a t -> ('a -> 'b t) -> 'b t

Monadic bind

val map : 'a t -> ('a -> 'b) -> 'b t

Functorial map

val run : 'a t -> 'a res

Running a monadic computation

module Infix : sig ... end

val float : float -> float t

float bound samples uniformly in 0; bound

val int : int -> int t

int bound samples uniformly in 0; bound-1

val bool : bool t

bool samples a boolean uniformly

val uniform : 'a array -> 'a t

uniform elts samples an element of the elts array by sampling an index uniformly.

raises Invalid_argument
if elts has length equal to 0

val bernouilli : float -> bool t

bernouilli alpha samples true with probability alpha.

raises Invalid_argument
if alpha is not in the 0;1 interval.

val geometric : float -> int t

geometric p samples a nonnegative integer according to the geometric law of parameter p.

raises Invalid_argument
if p <= 0 || p > 1

val subsample : n:int -> 'a t -> 'a t

subsample ~n gen samples one out of n samples from gen.

val of_empirical : 'a Stats_intf.emp -> 'a t

of_empirical emp samples from emp matching exactly the empirical frequencies.

val exponential : rate:float -> float t

Exponential distribution via inverse CDF.

raises Invalid_argument
if rate <=. 0.0.

val box_muller : mean:float -> std:float -> (float * float) t

Gaussian distribution via Box-Muller transform. Returns a pair of independent gaussian variates with prescribed mean and standard deviation.

raises Invalid_argument
if std <= 0.0

val gaussian : mean:float -> std:float -> float t

Gaussian distribution (wrapper over box-muller transform).

raises Invalid_argument
if std <= 0.0

val poisson : lambda:float -> int t

Poisson distribution via inverse transform. Consider using other methods for large lambda.

raises Invalid_argument
if lambda <= 0.0

val range : Stats_intf.range -> float t

Samples uniformly in the given range.

raises Invalid_argument
if range is empty.

val categorical : ('a * float) list -> 'a t

Categorical distribution. Total mass need not be one. Does not aggregate mass of equal elements.

raises Invalid_argument
if some weights are negative or if the total mass is zero.

val of_fin_mes : ('a, float) Stats_intf.fin_mes -> 'a t

Constructs a sampler from a finite measure through categorical. NB: this is mostly useful for sampling repeatedly from the distribution.

module Rational : sig ... end