nise {sm}

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, ...)

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.

Value

the integrated squared error.

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)