AbstractMCMC.sample(post::Comrade.Posterior, smplr::Nested, args...; kwargs...)

Sample the posterior post using NestedSamplers.jl Nested sampler. The args/kwargs are forwarded to NestedSampler for more information see its docs

This returns a tuple where the first element are the weighted samples from NestedSamplers in a TypedTable. The second element includes additional information about the samples, like the log-likelihood, evidence, evidence error, and the sample weights.

To create equally weighted samples the user can use ```julia using StatsBase chain, stats = sample(post, NestedSampler(dimension(post), 1000)) equalweightedchain = sample(chain, Weights(stats.weights), 10_000)