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
BIA	$\{0, 1\}^d$	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