Reproducible Example of Weighted Mean:
df = data.frame(x=rnorm(6), y=rnorm(6), c=runif(6))
df
x y c
1 -1.7474440 -0.31007446 0.05848928
2 -1.2224065 2.00200840 0.83287364
3 -0.2794127 -1.03566512 0.59140733
4 -0.3022496 0.05759183 0.05800232
5 0.4875809 0.88804664 0.36282380
6 -0.5468437 0.27501804 0.37218218
wt = c(5,5,4,1,3,5)/15 # This is the weight
wt
[1] 0.33333333 0.33333333 0.26666667 0.06666667 0.20000000
[6] 0.33333333
> weighted.mean(df$c,wt)
[1] 0.5992344
Weighted Mean R Documentation:
weighted.mean {stats} R Documentation
Weighted Arithmetic Mean
Description
Compute a weighted mean.
Usage
weighted.mean(x, w, ...)
## Default S3 method:
weighted.mean(x, w, ..., na.rm = FALSE)
Arguments
x
an object containing the values whose weighted mean is to be computed.
w
a numerical vector of weights the same length as x giving the weights to use for elements of x.
...
arguments to be passed to or from methods.
na.rm
a logical value indicating whether NA values in x should be stripped before the computation proceeds.
Details
This is a generic function and methods can be defined for the first argument x: apart from the default methods there are methods for the date-time classes "POSIXct", "POSIXlt", "difftime" and "Date". The default method will work for any numeric-like object for which [, multiplication, division and sum have suitable methods, including complex vectors.
If w is missing then all elements of x are given the same weight, otherwise the weights coerced to numeric by as.numeric and normalized to sum to one (if possible: if their sum is zero or infinite the value is likely to be NaN).
Missing values in w are not handled specially and so give a missing value as the result. However, zero weights are handled specially and the corresponding x values are omitted from the sum.
Value
For the default method, a length-one numeric vector.
See Also
mean
Examples
## GPA from Siegel 1994
wt <- c(5, 5, 4, 1)/15
x <- c(3.7,3.3,3.5,2.8)
xm <- weighted.mean(x, wt)