Sampling Functions

Listed below are the sampling methods for which functions are provided to simulating draws from distributions that can be specified up to constants of proportionalities. Model-based Sampler constructors are available for use with the mcmc() engine as well as stand-alone functions that can be used independently.

The following table summarizes the (d-dimensional) sample spaces over which each method simulates draws, whether draws are generated univariately or multivariately, and whether transformations are applied to map parameters to the sample spaces.

Summary of sampling methods and their characteristics.
    Model-Based Constructors Stand-Alone Functions
Method Sample Space Univariate Multivariate Transformations Univariate Multivariate
ABC \mathbb{R}^d No Yes Yes No No
AMM \mathbb{R}^d No Yes Yes No Yes
AMWG \mathbb{R}^d Yes No Yes Yes No
BHMC \{0, 1\}^d No Yes No No Yes
BMC3 \{0, 1\}^d Yes Yes No Yes Yes
BMG \{0, 1\}^d Yes Yes No Yes Yes
DGS Finite S \subset \mathbb{Z}^d Yes No No No Yes
HMC \mathbb{R}^d No Yes Yes No Yes
MALA \mathbb{R}^d No Yes Yes No Yes
MISS Parameter-defined Yes Yes No No No
NUTS \mathbb{R}^d No Yes Yes No Yes
RWM \mathbb{R}^d No Yes Yes No Yes
Slice S \subseteq \mathbb{R}^d Yes Yes Optional Yes Yes
SliceSimplex d-simplex No Yes No No Yes