sm (version 2.2-6.0)

nise: Integrated squared error between a density estimate and a Normal density

Description

This function evaluates the integrated squared error between a density estimate constructed from a standardised version of the univariate data y and a standard normal density function.

Usage

nise(y, ...)

Value

the integrated squared error.

Arguments

y

a vector of data.

...

further arguments which are to be passed to sm.options.

Details

The data y are first standardised to have sample mean 0 and sample variance 1. The integrated squared error between a density estimate constructed from these standardised data and a standard normal distribution is then evaluated.

See Section 2.5 of the reference below.

References

Bowman, A.W. and Azzalini, A. (1997). Applied Smoothing Techniques for Data Analysis: the Kernel Approach with S-Plus Illustrations. Oxford University Press, Oxford.

See Also

nmise

Examples

x <- rnorm(100)
nise(x)