package prbnmcn-dagger

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prbnmcn-dagger
- Dagger
  - Dist
  - Intf
    
    Core
    
    Infix
    
    Field
    
    Foldable
    
    Infix
    
    S
    
    Array_ops
    
    Infix
    
    List_ops
    
    Seq_ops
  - Lmh_incremental_inference
    
    Array_ops
    
    Infix
    
    List_ops
    
    Make_shared
    
    C
    
    Seq_ops
  - Lmh_inference
    
    Array_ops
    
    Infix
    
    List_ops
    
    Seq_ops
  - Log_space
  - RNG
  - Resampling
    
    Float_field
    
    Make
    
    F
    
    P
    
    Sampler
    
    Make_float
    
    P
    
    Particle
    
    S
  - Smc_inference
    
    Array_ops
    
    Infix
    
    Interruptible
    
    List_ops
    
    Non_interruptible
    
    Seq_ops
  - Stateful_sampling_monad
    
    Infix

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Library
Module
Module type
Parameter
Class
Class type

The Non_interruptible module exposes an implementation of Sequential Monte-Carlo that terminates when all particles terminate. Only use when the probabilistic program terminates almost surely!

val run : 
  ?resampling:resampling_strategy ->
  int ->
  'a t ->
  RNG.t ->
  ('a * Log_space.t) list

run ?resampling npart model rng_state runs sequential Monte-Carlo with npart initial particles. resampling defaults to systematic_resampling.

raises Invalid_population
if the total mass of the population becomes equal to Log_space.zero