MKLE-package {MKLE} | R Documentation |
Computes the maximum kernel likelihood estimator using fast fourier transforms.
Package: | MKLE |
Type: | Package |
Version: | 0.05 |
Date: | 2008-05-02 |
License: | GPL |
The maximum kernel likelihood estimator is defined to be the value hat theta that maximizes the estimated kernel likelihood based on the general location model,
f(x|theta) = f_{0}(x - theta).
This model assumes that the mean associated with $f_0$ is zero which of course implies that the mean of X_i is theta. The kernel likelihood is the estimated likelihood based on the above model using a kernel density estimate, hat f(.|h,X_1,...,X_n), and is defined as
hat L(theta|X_1,...,X_n) = prod_{i=1}^n hat f(X_{i}-(bar{X}-theta)|h,X_1,...,X_n).
The resulting estimator therefore is an estimator of the mean of X_i.
Thomas Jaki
Maintainer: Thomas Jaki <jaki.thomas@gmail.com>
Jaki T., West R. W. (2008) Maximum kernel likelihood estimation. Journal of Computational and Graphical Statistics Vol. 17(No 4), 976-993.
Silverman, B. W. (1986), Density Estimation for Statistics and Data Analysis, Chapman & Hall, 2nd ed.
data(state) mkle(state$CRIME)