hnorm {sm}R Documentation

Normal optimal choice of smoothing parameter in density estimation

Description

This functions evaluates the smoothing parameter which is asymptotically optimal for estimating a density function when the underlying distribution is Normal. Data in one, two or three dimensions can be handled.

Usage

hnorm(x)

Arguments

x a vector, or matrix with two or three columns, containing the data.

Details

see Section 2.4.2 of the reference below.

Value

the value of the Normal optimal smoothing parameter.

Side Effects

none

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

hcv, hsj

Examples

x <- rnorm(50)
hnorm(x)

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