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MALA

Purpose

MALA adds Langevin-style steps to MCMC proposals.

Full Sampling Section Keys

  • Sampling.Method (required): must be MALA.
  • Sampling.Variables (required):
  • name, description, distribution.type, distribution.parameters
  • runtime-safe parameter sets: Flat(min,max), Log(min,max), Normal(mean,stddev), Log-Normal(mean,stddev), Logit(location,scale)
  • Sampling.LogLikelihood (required): array of {name, expression}
  • Sampling.selection (optional, string)
  • Sampling.Bounds:
  • base keys: num_chains, num_iters, proposal_scale
  • MALA keys:
    • mala_step_size (optional, number, default 0.1)
    • step_size (optional, number, alias)

Full Skeleton

Sampling:
  Method: "MALA"
  Variables:
    - name: x
      description: variable x
      distribution:
        type: Flat
        parameters:
          min: -5
          max: 5
  LogLikelihood:
    - name: L_x
      expression: "-0.5*(x/1.0)^2"
  Bounds:
    num_chains: 6
    num_iters: 9000
    proposal_scale: [0.08, 0.08, 0.08, 0.08, 0.08, 0.08]
    mala_step_size: 0.05
    step_size: 0.05

Example

Sampling:
  Method: "MALA"
  Variables:
    - name: x
      description: variable x
      distribution:
        type: Flat
        parameters:
          min: -5
          max: 5
  LogLikelihood:
    - name: L_x
      expression: "-0.5*(x/1.0)^2"
  Bounds:
    num_chains: 6
    num_iters: 9000
    proposal_scale: [0.08, 0.08, 0.08, 0.08, 0.08, 0.08]
    mala_step_size: 0.05