mean integrated squared error for density estimation with normal data
This function evaluates the mean integrated squared error of a density estimate which is constructed from data which follow a normal distribution.
nmise(sd, n, h)
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. |
see Section 2.4 of the reference below.
the mean integrated squared error of the density estimate.
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(50) sd <- sqrt(var(x)) n <- length(x) h <- seq(0.1, 2, length=32) plot(h, nmise(sd, n, h), type = "l")
Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.