MC_neff_theoretical_stable: Compute the "stable" theoretical effective sample size in...

In maxbiostat/BinaryMarkovChains: Utilities for Two-State Discrete-Time Markov Chains

Compute the "stable" theoretical effective sample size in two-state Markov chain.

Description

This is the stabilised theoretical effective sample size for a sample of size N given parameters alpha and p.

Usage

MC_neff_theoretical_stable(N, alpha, p)

Arguments

N	number of iterations
alpha	a transition probability (between 0 and 1)
p	(marginal) success probability leads to a cap of 50*N on MC_ess_theoretical_stable.

Details

This version returns a maximum ESS of N*log10(N). different outputs. It is very similar to MC_neff_theoretical in most practical situations.

Value

effective sample size

See Also

MC_neff_theoretical

Examples

p <- .25
MC_neff_theoretical_stable(N = 100, alpha = p, p = p) ## independent sampling gives N_eff = N

maxbiostat/BinaryMarkovChains documentation built on Dec. 11, 2023, 4:29 a.m.