package prbnmcn-dagger-stats

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Class type
type state = Random.State.t
type !'a t = state -> 'a
type !'a res = state -> 'a
val return : 'a -> 'a t
val bind : 'a t -> ('a -> 'b t) -> 'b t
val map : 'a t -> ('a -> 'b) -> 'b t
val run : 'a t -> 'a res
module Infix : sig ... end
val iid : 'a t -> 'a Seq.t t
val float : float -> float t
val int : int -> int t
val bool : bool t
val shuffle : 'a array -> 'a array t
val uniform : 'a array -> 'a t
val bernoulli : float -> bool t
val geometric : float -> int t
val subsample : n:int -> 'a t -> 'a t
val of_empirical : 'a array -> 'a t
val exponential : rate:float -> float t
val box_muller : mean:float -> std:float -> (float * float) t
val gaussian : mean:float -> std:float -> float t
val poisson : lambda:float -> int t
val range : Stats__Stats_intf.range -> float t
val rectangle : min:float array -> max:float array -> float array t
val gamma : shape:float -> scale:float -> float t
val categorical : ('a * float) array -> 'a t
val without_replacement : int -> 'a list -> ('a list * 'a list) t
val tup2 : 'a t -> 'b t -> ('a * 'b) t
val tup3 : 'a t -> 'b t -> 'c t -> ('a * 'b * 'c) t
val tup4 : 'a t -> 'b t -> 'c t -> 'd t -> ('a * 'b * 'c * 'd) t
val tup5 : 'a t -> 'b t -> 'c t -> 'd t -> 'e t -> ('a * 'b * 'c * 'd * 'e) t
val tup6 : 'a t -> 'b t -> 'c t -> 'd t -> 'e t -> 'f t -> ('a * 'b * 'c * 'd * 'e * 'f) t
val mixture : float array -> (int -> 'b t) -> 'b t
module Rational : sig ... end
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