R: Integrated squared error between a density estimate and a...

nise {sm} | R Documentation

## 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)

[Package sm version 2.2-5.4 Index]