IQR

0th

Percentile

The Interquartile Range

computes interquartile range of the x values.

Keywords
robust, distribution, univar
Usage
IQR(x, na.rm = FALSE, type = 7)
Arguments
x

a numeric vector.

na.rm

logical. Should missing values be removed?

type

an integer selecting one of the many quantile algorithms, see quantile.

Details

Note that this function computes the quartiles using the quantile function rather than following Tukey's recommendations, i.e., IQR(x) = quantile(x, 3/4) - quantile(x, 1/4).

For normally \(N(m,1)\) distributed \(X\), the expected value of IQR(X) is 2*qnorm(3/4) = 1.3490, i.e., for a normal-consistent estimate of the standard deviation, use IQR(x) / 1.349.

References

Tukey, J. W. (1977). Exploratory Data Analysis. Reading: Addison-Wesley.

See Also

fivenum, mad which is more robust, range, quantile.

Aliases
  • IQR
Examples
library(stats) # NOT RUN { IQR(rivers) # }
Documentation reproduced from package stats, version 3.5.0, License: Part of R 3.5.0

Community examples

Looks like there are no examples yet.