| nise {sm} | R Documentation |
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.
nise(y, hmult=1)
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. |
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.
the integrated squared error.
Bowman, A.W. and Azzalini, A. (1997). Applied Smoothing Techniques for Data Analysis: the Kernel Approach with S-Plus Illustrations. Oxford University Press, Oxford.
x <- rnorm(100) nise(x)