Compute Numerical Standard Error and Relative Numerical Efficiency
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).
numEff(x, m = as.integer(min(length(x),(100/sqrt(5000))*sqrt(length(x)))))
x |
R x 1 vector of draws |
m |
number of lags for autocorrelations |
default for number of lags is chosen so that if R=5000, m=100 and increases as the sqrt(R).
A list containing:
stderr |
standard error of the mean of x |
f |
variance ratio (relative numerical efficiency) |
This routine is a utility routine that does not check the input arguments for proper dimensions and type.
Peter Rossi, Anderson School, UCLA, perossichi@gmail.com.
For further discussion, see Chapter 3, Bayesian Statistics and Marketing by Rossi, Allenby, and McCulloch.
http://www.perossi.org/home/bsm-1
numEff(rnorm(1000), m=20) numEff(rnorm(1000))
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