Public API

ARS.ARSampler — Method
ARSampler(
    obj::ARS.Objective{F<:Function, G<:Function},
    initial_points::Array{T<:AbstractFloat, 1},
    domain::Tuple{T<:AbstractFloat, T<:AbstractFloat}
) -> ARS.ARSampler{T, F, G} where {T<:AbstractFloat, F<:Function, G<:Function}

Initialize an adaptive rejection sampler over a (log) objective function from obj. initial_points should be a vector of abscissae defining the initial segments of the sampler. At least 2 of the points should be on opposite sides of the objective function's maximum.

ARSampler(obj, initial_points, domain)

defined at /home/runner/work/ARS.jl/ARS.jl/src/ARS.jl:321.

ARS.Objective — Type
Objective(f)
Objective(f, adbackend)
Objective(f, adbackend, init)

Create an Objective for a function automatically generating its gradient. Gradients are calculated using DifferentiationInterface.jl using the backend of choice with Mooncake.jl being the default. In order to prepare the gradient an initial value is required. By default this is one(Float64). If a gradient for a different type is desired, it should be specified.

Warning

Observe that f should be in its log-concave form and that no checks are performed in order to verify this.

Example

# Create a sampler using `Mooncake.jl` autodiff and Float32 as its eltype
ARS.Objective(somefun, AutoMooncake(; config=nothing), one(Float32))
# Create a sampler using `AutoDiff.jl` autodiff and the default Float64 as its eltype
ARS.Objective(somefun, AutoForwardDiff())
ARS.Objective — Method
Objective(f::Function, grad::Function) -> ARS.Objective

Create an Objective directly defined by its function f and custom gradient grad.

Warning

Observe that f should be in its log-concave form and that no checks are performed in order to verify this.

ARS.sample! — Function
sample!([rng=default_rng()], s::ARSampler, n::Integer, add_segments::Bool=true)
sample!([rng=default_rng()], v::AbstractVector, s::ARSampler, add_segments::Bool=true)

Draw samples from s. If supplied, a vector v will be filled with samples. Otherwise the number of samples is specified with n.