weightedQuantile: Weighted Quantiles.

In petersenlab: A Collection of R Functions by the Petersen Lab

Weighted Quantiles.

Description

Computes weighted quantiles. whdquantile() uses a weighted Harrell-Davis quantile estimator. wthdquantile() uses a weighted trimmed Harrell-Davis quantile estimator. wquantile() uses a weighted traditional quantile estimator.

Usage

kish_ess(w)

wquantile_generic(x, w, probs, cdf)

whdquantile(x, w, probs)

wthdquantile(x, w, probs, width = 1/sqrt(kish_ess(w)))

wquantile(x, w, probs, type = 7)

Arguments

w	Numeric vector of weights to give each value. Should be the same length as the vector of values.
x	Numeric vector of values of which to determine the quantiles.
probs	Numeric vector of the quantiles to retrieve.
cdf	Cumulative distribution function.
width	Numeric value for the width of the interval in the trimmed Harrell-Davis quantile estimator.
type	Numeric value for type of weighted quantile.

Details

Computes weighted quantiles according to Akinshin (2023).

Value

Numeric vector of specified quantiles.

See Also

\Sexpr[results=rd]{tools:::Rd_expr_doi("10.48550/arXiv.2304.07265")}

Other computations: Mode(), meanSum(), mySum()

Examples

mydata <- c(1:100, 1000)
mydataWithNAs <- mydata
mydataWithNAs[c(1,5,7)] <- NA
weights <- rep(1, length(mydata))
quantiles <- c(0.01, 0.05, 0.1, 0.25, 0.5, 0.75, 0.9, 0.95, 0.99)

whdquantile(
  x = mydata,
  w = weights,
  probs = quantiles)

wthdquantile(
  x = mydata,
  w = weights,
  probs = quantiles)

wquantile(
  x = mydata,
  w = weights,
  probs = quantiles)

whdquantile(
  x = mydataWithNAs,
  w = weights,
  probs = quantiles)

wthdquantile(
  x = mydataWithNAs,
  w = weights,
  probs = quantiles)

wquantile(
  x = mydataWithNAs,
  w = weights,
  probs = quantiles)

petersenlab documentation built on April 4, 2025, 12:22 a.m.