running_mean

Computes running mean of a vector or matrix, returning the values from each step.

Fast functions for effective sample size, weighted multivariate
mean, variance, and quantile computation, and weight diagnostic plot for
generic importance sampling type or other probability weighted samples.

Jouni Helske

diagis

Diagnostic Plot and Multivariate Summary Statistics of Weighted
Samples from Importance Sampling

running_mean function

<dl><dt>x</dt>
<dd>A numeric vector, matrix, three dimensional array, or an <code>mcmc</code> object from
the <code>coda</code> package. For matrix, the mean is computed for each column, and 
for array the sweep is done over the third dimension.</dd>
<dt>na.rm</dt>
<dd>If <code>TRUE</code>, <code>NA</code> values in <code>x</code> are
omitted from the computation. Default is <code>FALSE</code>.</dd></dl>

Arguments

Running mean — running_mean

<dl>

<dt>x</dt>
<dd>A numeric vector, matrix, three dimensional array, or an <code>mcmc</code> object from
the <code>coda</code> package. For matrix, the mean is computed for each column, and 
for array the sweep is done over the third dimension.</dd>


<dt>na.rm</dt>
<dd>If <code>TRUE</code>, <code>NA</code> values in <code>x</code> are
omitted from the computation. Default is <code>FALSE</code>.</dd>

</dl>

running_mean: Running mean

Description

Usage

Value

Arguments