weighted_quantile

Computes a weighted quantiles of a vector or matrix. Based on the formula in 
Wikipedia (see the vignette) which is one of many ways to compute weighted 
quantiles.

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_quantile function

<dl><dt>x</dt>
<dd>A numeric vector or matrix. For matrix, the quantiles 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>probs</dt>
<dd>A numeric vector of probabilities with values between 0 and 1.</dd>
<dt>na.rm</dt>
<dd>If <code>TRUE</code>, <code>NA</code> and <code>NaN</code> values in <code>x</code> 
(and corresponding weights in <code>w</code>) are omitted from the computation. 
Default is <code>FALSE</code>. Additional missing values in <code>w</code> are not 
allowed.</dd></dl>

Arguments

Weighted quantiles — weighted_quantile

<dl>

<dt>x</dt>
<dd>A numeric vector or matrix. For matrix, the quantiles 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>probs</dt>
<dd>A numeric vector of probabilities with values between 0 and 1.</dd>


<dt>na.rm</dt>
<dd>If <code>TRUE</code>, <code>NA</code> and <code>NaN</code> values in <code>x</code> 
(and corresponding weights in <code>w</code>) are omitted from the computation. 
Default is <code>FALSE</code>. Additional missing values in <code>w</code> are not 
allowed.</dd>

</dl>

weighted_quantile: Weighted quantiles

Description

Usage

Value

Arguments