AdvancedMH.jl

MetropolisHastings{D}

MetropolisHastings has one field, proposal. proposal is a Proposal, NamedTuple of Proposal, or Array{Proposal} in the shape of your data. For example, if you wanted the sampler to return a NamedTuple with shape

x = (a = 1.0, b=3.8)

The proposal would be

proposal = (a=StaticProposal(Normal(0,1)), b=StaticProposal(Normal(0,1)))
````

Other allowed proposals are

p1 = StaticProposal(Normal(0,1)) p2 = StaticProposal([Normal(0,1), InverseGamma(2,3)]) p3 = StaticProposal((a=Normal(0,1), b=InverseGamma(2,3))) p4 = StaticProposal((x=1.0) -> Normal(x, 1))

The sampler is constructed using

julia spl = MetropolisHastings(proposal) ```

When using MetropolisHastings with the function sample, the following keyword arguments are allowed:

• initial_params defines the initial parameterization for your model. If

none is given, the initial parameters will be drawn from the sampler's proposals.

• param_names is a vector of strings to be assigned to parameters. This is only

used if chain_type=Chains.

• chain_type is the type of chain you would like returned to you. Supported

types are chain_type=Chains if MCMCChains is imported, or chain_type=StructArray if StructArrays is imported.

DensityModel{F} <: AbstractModel

DensityModel wraps around a self-contained log-liklihood function logdensity.

Example:

l(x) = logpdf(Normal(), x)
DensityModel(l)