mean integrated squared error for density estimation with normal data
Usage
nmise(sd, n, h)
Arguments
sd
|
the standard deviation of the normal distribution from which the data arise.
|
n
|
the sample size of the data.
|
h
|
the smoothing parameter used to construct the density estimate.
|
Description
This function evaluates the mean integrated squared error of a density
estimate which is constructed from data which follow a normal distribution.Details
see Section 2.4 of the reference below.Value
the mean integrated squared error of the density estimate.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
nise
Examples
x <- rnorm(50)
sd <- sqrt(var(x))
n <- length(x)
h <- seq(0.1, 2, length=32)
plot(h, nmise(sd, n, h), type = "l")