package prbnmcn-dagger-gsl

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module Log_space = Dagger.Log_space
val gsl_rng : Gsl.Rng.rng_type Stdlib.ref
val rng_of_lxm : PRNG.LXM.State.t -> Gsl.Rng.t
val dist0 : (Gsl.Rng.t -> 'a) -> ('a -> Dagger.Log_space.t) -> 'a Dagger.Dist.t
val dist1 : ('a -> Gsl.Rng.t -> 'b) -> ('a -> 'b -> Dagger.Log_space.t) -> 'a -> 'b Dagger.Dist.t
val dist2 : ('a -> 'b -> Gsl.Rng.t -> 'c) -> ('a -> 'b -> 'c -> Dagger.Log_space.t) -> 'a -> 'b -> 'c Dagger.Dist.t
val kernel1 : ('a -> 'b -> Gsl.Rng.t -> 'b) -> ('a -> 'b -> 'b -> Dagger.Log_space.t) -> 'b -> 'a -> 'b Dagger.Dist.t
val float : float -> float Dagger.Dist.t
val int : int -> int Dagger.Dist.t
val bool : int Dagger.Dist.t
val gaussian : mean:float -> std:float -> float Dagger.Dist.t
val gaussian_tail : a:float -> std:float -> float Dagger.Dist.t
val laplace : a:float -> float Dagger.Dist.t
val exppow : a:float -> b:float -> float Dagger.Dist.t
val cauchy : a:float -> float Dagger.Dist.t
val rayleigh : sigma:float -> float Dagger.Dist.t
val rayleigh_tail : a:float -> sigma:float -> float Dagger.Dist.t
val landau : float Dagger.Dist.t
val gamma : a:float -> b:float -> float Dagger.Dist.t
val weibull : a:float -> b:float -> float Dagger.Dist.t
val flat : float -> float -> float Dagger.Dist.t
val bernoulli : bias:float -> bool Dagger.Dist.t
val binomial : float -> int -> int Dagger.Dist.t
val geometric : p:float -> int Dagger.Dist.t
val exponential : rate:float -> float Dagger.Dist.t
val poisson : rate:float -> int Dagger.Dist.t
val categorical : (module Stdlib.Hashtbl.S with type key = 'a) -> ('a * float) array -> 'a Dagger.Dist.t
val beta : a:float -> b:float -> float Dagger.Dist.t
val dirichlet : alpha:float array -> float array Dagger.Dist.t
val lognormal : zeta:float -> sigma:float -> float Dagger.Dist.t
val chi_squared : nu:float -> float Dagger.Dist.t
val mixture : float array -> 'a Dagger.Dist.t array -> 'a Dagger.Dist.t
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