bhpm.monitor.samples: Generate a template for choosing which samples to monitor.

In bhpm: Bayesian Hierarchical Poisson Models for Multiple Grouped Outcomes with Clustering

Description

This function generate a template for choosing which samples to monitor based on the model and hierarchy. As some of the MCMC model simulations require large amounts of memory choosing not to monitor samples reduced the overall memory footprint.

Usage

	bhpm.monitor.samples(model = "1a", hier = 3)

Arguments

model	Allowed values are "1a" and "BB". "BB" models include a point-mass.
hier	Allowed values are 2 and 3. Generate a template for a 2 or 3 level hierarchy.

Value

A dataframe containing two columns:

variable: the name of a class of variables e.g. "theta" monitor: 0 - don't monitor, 1 - monitor.

Author(s)

R. Carragher

Examples

mon <- bhpm.monitor.samples("1a", hier = 3)
print(mon)

mon <- bhpm.monitor.samples("1a", hier = 3)
print(mon)

bhpm documentation built on April 1, 2020, 5:09 p.m.