IQrange

0th

Percentile

The Interquartile Range

Computes (standardized) interquartile range of the x values.

Keywords
robust, distribution, univar
Usage
IQrange(x, na.rm = FALSE, type = 7)
sIQR(x, na.rm = FALSE, type = 7, constant = 2*qnorm(0.75))
Arguments
x

a numeric vector.

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 quantile.

constant

standardizing contant; see details below.

Details

This function IQrange computes quartiles as IQR(x) = quantile(x,3/4) - quantile(x,1/4). The function is identical to function IQR. It was added before the type argument was introduced to function IQR in 2010 (r53643, r53644).

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. This is implemented in function sIQR (standardized IQR).

References

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

See Also

quantile, IQR.

Aliases
  • IQrange
  • sIQR
Examples
# NOT RUN {
IQrange(rivers)

## identical to
IQR(rivers)

## other quantile algorithms
IQrange(rivers, type = 4)
IQrange(rivers, type = 5)

## standardized IQR
sIQR(rivers)

## right-skewed data distribution
sd(rivers)
mad(rivers)

## for normal data
x <- rnorm(100)
sd(x)
sIQR(x)
mad(x)
# }
Documentation reproduced from package MKdescr, version 0.4, License: LGPL-3

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