rcondbern: Conditional Bernoulli distribution

In nianqiaoju/agents: Toolkit for inference in agent-based modelss

Description

Gives one sample from the conditional Bernoulli distribution, either with exact method or with MCMC. This function is a wrapper for idchecking_cpp and metropolis_condbern_cpp

Usage

rcondbern(sum_x, alpha, exact = TRUE, num_sample = NULL)

Arguments

sum_x	sum of the Bernoullis
alpha	vector of success probabilities
exact	binary, if TRUE, then use id-check sampling, otherwise use the metropolis algorithm. Default is TRUE.
num_sample	default is NULL.

Value

sample, a length N binary vector, with 1 at the chosen entry

nianqiaoju/agents documentation built on Feb. 19, 2021, 12:18 a.m.