View source: R/weightedStats.R
| weighted.median | R Documentation |
Compute the median, quantiles or variance of a set of numbers which have weights associated with them.
weighted.median(x, w, na.rm = TRUE, type=2, collapse=TRUE)
weighted.quantile(x, w, probs=seq(0,1,0.25), na.rm = TRUE, type=4, collapse=TRUE)
weighted.var(x, w, na.rm = TRUE)
x |
Data values. A vector of numeric values, for which the median or quantiles are required. |
w |
Weights.
A vector of nonnegative numbers, of the same length as |
probs |
Probabilities for which the quantiles should be computed. A numeric vector of values between 0 and 1. |
na.rm |
Logical. Whether to ignore |
type |
Integer specifying the rule for calculating the median or quantile,
corresponding to the rules available for
|
collapse |
Research use only. |
The ith observation x[i] is treated as having
a weight proportional to w[i].
The weighted median is a value m
such that the total weight of data less than or equal to m
is equal to half the total weight. More generally, the weighted quantile with
probability p is a value q
such that the total weight of data less than or equal to q
is equal to p times the total weight.
If there is no such value, then
if type=1, the next largest value is returned
(this is the right-continuous inverse of the left-continuous
cumulative distribution function);
if type=2, the average of the two surrounding values is
returned (the average of the right-continuous and left-continuous
inverses);
if type=4, linear interpolation is performed.
Note that the default rule for weighted.median is
type=2, consistent with the traditional definition of the median,
while the default for weighted.quantile is type=4.
A numeric value or vector.
.
quantile, median.
x <- 1:20
w <- runif(20)
weighted.median(x, w)
weighted.quantile(x, w)
weighted.var(x, w)
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