Normal optimal choice of smoothing parameter in density estimation
Usage
hnorm(x)
Arguments
x
a vector, or matrix with two or three columns, containing the data.
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.
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.