Compute Censored Empirical Likelihood Ratio by Sequential Quadratic Programming

نویسنده

  • Kun Chen
چکیده

Empirical likelihood ratio method (Thomas and Grunkmier 1975, Owen 1988, 1990, 2001) is a general nonparametric inference procedure that has many nice properties. Recently the procedure has been shown to also work with censored data with various parameters and the nice properties also hold there. But the computation of the empirical likelihood ratios with censored data and/or complex setting is often non-trivial. We propose to use sequential quadratic programming (SQP) method to overcome the computational problem. Examples are given in the following cases: (1) right censored data with a parameter of mean; (2) Interval censored data.

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تاریخ انتشار 2002