using Distributions, Klara

p = BasicContUnvParameter(:p, pdf=Normal())

model = likelihood_model([p], isindexed=false)

mcsampler = AM(1.)

tuner = VanillaMCTuner()

mcrange = BasicMCRange(nsteps=10000, burnin=1000)

v0 = Dict(:p=>3.11)

outopts = Dict(:monitor=>[:value, :logtarget], :diagnostics=>[:accept])

job = BasicMCJob(model, mcsampler, mcrange, v0, outopts=outopts)

@time run(job)

chain = output(job)

mean(chain)

acceptance(chain)
