ESS {astsa} | R Documentation |
Effective Sample Size (ESS)
Description
Estimates the ESS of a given vector of samples.
Usage
ESS(trace, tol = 1e-08, BIC = TRUE)
Arguments
trace |
vector of sampled values from an MCMC run (univariate only) |
tol |
ESS is returned as zero if the estimated spectrum at frequency zero is less than this value |
BIC |
if TRUE (default), |
Details
Uses spec.ic
to estimate the spectrum of the input at frequency zero (spec0
). Then, ESS is estimated as
ESS = length(trace)*var(trace)/spec0
.
Value
Returns the estimated ESS of the input.
Author(s)
D.S. Stoffer
References
You can find demonstrations of astsa capabilities at FUN WITH ASTSA.
The most recent version of the package can be found at https://github.com/nickpoison/astsa/.
In addition, the News and ChangeLog files are at https://github.com/nickpoison/astsa/blob/master/NEWS.md.
The webpages for the texts and some help on using R for time series analysis can be found at https://nickpoison.github.io/.
Examples
# Fit an AR(2) to the Recruitment series
u = ar.mcmc(rec, porder=2, n.iter=1000, plot=FALSE)
# then calculate the ESSs
apply(u, 2, ESS)