MKLE-package {MKLE} | R Documentation |
Computes the maximum kernel likelihood estimator using fast fourier transforms.
Package: | MKLE |
Type: | Package |
Version: | 0.03 |
Date: | 2007-08-14 |
License: | GNU |
The maximum kernel likelihood estimator is defined to be the value $hattheta_h$ 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. (2007) Maximum kernel likelihood estimation. Submitted to textit{Journal of Computational and Graphical Statistics}.
Silverman, B. W. (1986), textit{Density Estimation for Statistics and Data Analysis}, Chapman & Hall, 2nd ed.
data(state) mkle(state$CRIME)