weighted_se

Computes a weighted standard error of a vector or matrix.

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

weighted_se function

<dl><dt>x</dt>
<dd>A numeric vector or matrix. For matrix, standard errors are 
computed for each column</dd>
<dt>w</dt>
<dd>A numeric vector of non-negative weights. Will be automatically normalised to sum to one.</dd>
<dt>na.rm</dt>
<dd>If <code>TRUE</code>, <code>NA</code> values in <code>x</code> (and corresponding weights in <code>w</code>) are
omitted from the computation. Default is <code>FALSE</code>.</dd></dl>

Arguments

Weighted standard error — weighted_se

<dl>

<dt>x</dt>
<dd>A numeric vector or matrix. For matrix, standard errors are 
computed for each column</dd>


<dt>w</dt>
<dd>A numeric vector of non-negative weights. Will be automatically normalised to sum to one.</dd>


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

</dl>

weighted_se: Weighted standard error

Description

Usage

Value

Arguments