summary.XDNUTS {XDNUTS}R Documentation

Function to print the summary of an XDNUTS model.

Description

Function to print the summary of an XDNUTS model.

Usage

## S3 method for class 'XDNUTS'
summary(
  object,
  ...,
  q.val = c(0.05, 0.25, 0.5, 0.75, 0.95),
  which = NULL,
  which_chains = NULL,
  digits = 5
)

Arguments

object

an object of class XDNUTS.

...

additional arguments to customize the summary.

q.val

desired quantiles of the posterior distribution for each coordinate. Default values are 0.05,0.25,0.5,0.75,0.95.

which

either a numerical vector indicating the index of the parameters of interest or a string

which = 'continuous'

for plotting the first d-k parameters.

which = 'discontinuous'

for plotting the last k parameters.

where both d and k are elements contained in the output of the function xdnuts.

which_chains

a numerical vector indicating the index of the chains of interest.

digits

number of digits in the summary table.

Value

a list containing a data frame named stats with the following columns:

mean

the mean of the posterior distribution.

sd

the standard deviation of the posterior distribution.

q.val

the desired quantiles of the posterior distribution.

ESS

the Effective Sample Size for each marginal distribution.

R_hat

the Potential Scale Reduction Factor of Gelman (Gelman and Rubin 1992), only if multiple chains are available.

R_hat_upper_CI

the upper confidence interval for the latter, only if multiple chains are available.

Other quantities returned are:

Gelman.Test

the value of the multivariate Potential Scale Reduction Factor test (Gelman and Rubin 1992).

BFMI

the value of the empirical Bayesian Fraction of Information Criteria (Betancourt 2016). A value below 0.2 indicates a bad random walk behavior in the energy Markov Chain, mostly due to a suboptimal specification of the momentum parameters probability density.

References

Betancourt M (2016). “Diagnosing suboptimal cotangent disintegrations in Hamiltonian Monte Carlo.” arXiv preprint arXiv:1604.00695.

Gelman A, Rubin DB (1992). “Inference from iterative simulation using multiple sequences.” Statistical science, 7(4), 457–472.


[Package XDNUTS version 1.2 Index]