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, hmult=1)
Arguments
y
a vector of data.
hmult
a factor which can be used to multiply the normal optimal smoothing parameter
before construction of the density estimate.
Value
the integrated squared error.
synopsis
nise(y, ...)
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.