numEff: Compute Numerical Standard Error and Relative Numerical...

In bayesm: Bayesian Inference for Marketing/Micro-Econometrics

Compute Numerical Standard Error and Relative Numerical Efficiency

Description

numEff computes the numerical standard error for the mean of a vector of draws as well as the relative numerical efficiency (ratio of variance of mean of this time series process relative to iid sequence).

Usage

numEff(x, m = as.integer(min(length(x),(100/sqrt(5000))*sqrt(length(x)))))

Arguments

x	R x 1 vector of draws
m	number of lags for autocorrelations

Details

default for number of lags is chosen so that if R=5000, m=100 and increases as the sqrt(R).

Value

A list containing:

stderr	standard error of the mean of x
f	variance ratio (relative numerical efficiency)

Warning

This routine is a utility routine that does not check the input arguments for proper dimensions and type.

Author(s)

Peter Rossi, Anderson School, UCLA, [e-mail].

References

For further discussion, see Chapter 3, Bayesian Statistics and Marketing by Rossi, Allenby, and McCulloch.

Examples

numEff(rnorm(1000), m=20)
numEff(rnorm(1000))

bayesm documentation built on Sept. 24, 2023, 1:07 a.m.