zscore {MKdescr} | R Documentation |
Compute z-Scores
Description
The functions compute the classical z-score as well as two robust versions of z-scores.
Usage
zscore(x, na.rm = FALSE)
medZscore(x, na.rm = FALSE, constant = 1/qnorm(0.75))
iqrZscore(x, na.rm = FALSE, type = 7, constant = 2*qnorm(0.75))
Arguments
x |
numeric vector with positive numbers. |
na.rm |
logical. Should missing values be removed? |
type |
an integer between 1 and 9 selecting one of nine quantile
algorithms; for more details see |
constant |
Details
The functions compute the (classical) zscore as well as two robust variants.
medZscore
uses the (standardized) MAD instead of SD and median instead of mean.
iqrZscore
uses the (standardized) IQR instead of SD and median instead of mean.
Value
z-score.
Author(s)
Matthias Kohl Matthias.Kohl@stamats.de
Examples
## 10% outliers
out <- rbinom(100, prob = 0.1, size = 1)
sum(out)
x <- (1-out)*rnorm(100, mean = 10, sd = 2) + out*25
z <- zscore(x)
z.med <- medZscore(x)
z.iqr <- iqrZscore(x)
## mean without outliers (should by close to 0)
mean(z[!out])
mean(z.med[!out])
mean(z.iqr[!out])
## sd without outliers (should by close to 1)
sd(z[!out])
sd(z.med[!out])
sd(z.iqr[!out])
[Package MKdescr version 0.8 Index]