esr_pars: Effective Sampling Rate for Parameters

In universals: S3 Generics for Bayesian Analyses

Effective Sampling Rate for Parameters

Description

Calculates the effective sampling rate (esr) for each parameter.

Usage

esr_pars(x, ...)

Arguments

x	An object.
...	Other arguments passed to methods.

Details

By default

\frac{1}{1 + 2 ∑_{k = 1}^∞ρ_k(θ)}

from Brooks et al. (2011) where the infinite sum is truncated at lag k when ρ_{k+1}(θ) < 0.

Value

A uniquely named numeric vector of values between 0 and 1 indicating the esr value for each parameter.

References

Brooks, S., Gelman, A., Jones, G.L., and Meng, X.-L. (Editors). 2011. Handbook for Markov Chain Monte Carlo. Taylor & Francis, Boca Raton.

See Also

Other convergence: converged_pars(), converged_terms(), converged(), esr_terms(), esr(), rhat_pars(), rhat_terms(), rhat()

universals documentation built on Sept. 22, 2022, 5:07 p.m.