esr_pars: Effective Sampling Rate for Parameters

In poissonconsulting/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 \sum_{k = 1}^\infty\rho_k(\theta)}

from Brooks et al. (2011) where the infinite sum is truncated at lag k when \rho_{k+1}(\theta) < 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(), converged_pars(), converged_terms(), esr(), esr_terms(), rhat(), rhat_pars(), rhat_terms()

poissonconsulting/universals documentation built on June 9, 2025, 1:58 p.m.