Mean Empirical Likelihood

Empirical likelihood ratio test for median and mean residual lifetime.

Prompted by several recent papers on the inference on median and mean residual life time, we note that the testing involving the mean or median residual life function in censored survival data can be obtained by an easy application of the general empirical likelihood ratio test. This approach has several advantages: (1) There is no need to estimate the variance/covariance at all, which may beco...

Calibration of the Empirical Likelihood Method for a Vector Mean

The empirical likelihood method is a versatile approach for testing hypotheses and constructing confidence regions in a non-parametric setting. For testing the value of a vector mean, the empirical likelihood method offers the benefit of making no distributional assumptions beyond some mild moment conditions. However, in small samples or high dimensions the method is very poorly calibrated, pro...

Inferences about the Population Mean: Empirical Likelihood versus Bootstrap-t

Empirical Likelihood

Empirical likelihood is a technique for forming hypothesis tests and conndence sets based on nonparametric likelihood ratios. Many properties of parametric likelihood ratio functions have nonparametric parallels. The main one is that there is a nonparametric version of Wilks's famous result wherein an asymptotic chisquare distribution holds for the log likelihood ratio. The nonparametric versio...

Mean likelihood frequency estimation

Estimation of signals with nonlinear as well as linear parameters in noise is studied. Maximum likelihood estimation has been shown to perform the best among all the methods. In such problems, joint maximum likelihood estimation of the unknown parameters reduces to a separable optimization problem, where first, the nonlinear parameters are estimated via a grid search, and then, the nonlinear pa...