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MeanAD: Mean Absolute Deviation From a Center Point

Description

Calculates the mean absolute deviation from a center point, typically the sample mean or the median.

Usage

MeanAD(x, weights = NULL, center = Mean, na.rm = FALSE)

Arguments

x

a vector containing the observations.

weights

a numerical vector of weights the same length as x giving the weights to use for elements of x.

center

a single numerical value or the name of a function to be used as center. Can as well be a self defined function. Default is Mean().

na.rm

a logical value indicating whether or not missing values should be removed. Defaults to FALSE.

Value

Numeric value.

Details

The MeanAD function calculates the mean absolute deviation from the mean value (or from another supplied center point) of x, after having removed NA values (if requested): $$\frac{1}{n} \cdot \sum_{i=1}^{n}\left | x_{i}-c \right | \; \; \; \textup{where} \; c=mean(x) \; \textup{or} \; c=med(x)$$

The function supports the use of weights. The default function for the center value Mean() has a weights arguments, too. If a user defined function is used it must be assured that it has a weights argument.

See Also

mad

Examples

Run this code
# NOT RUN {
x <- runif(100)
MeanAD(x)

speed <- c(58, 88, 40, 60, 72, 66, 80, 48, NA)
MeanAD(speed)
MeanAD(speed, na.rm=TRUE)


# using the median as centerpoint
x <- c(2,3,5,3,1,15,23)

MeanAD(x, center=mean)
MeanAD(x, center=median)

# define a fixed center
MeanAD(x, center=4)

# use of weights
MeanAD(x=0:6, weights=c(21,46,54,40,24,10,5))
# }

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