Efficient Algorithms for Computing the Non- and Semi-Parametric Maximum Likelihood Estimates of Panel Count Data
نویسندگان
چکیده
Non-parametric and semi-parametric analysis of panel count data have recently been an active research topic in statistical literature. Maximum likelihood method based on non-homogeneous Poisson process has been proved an efficient inference procedure for such analysis. However, computing the nonand semi-parametric maximum likelihood estimates (MLE) can be very intensive numerically. In this manuscript, we develop an efficient numerical algorithm stemmed from the Newton-Raphson method to compute the nonand semi-parametric MLE for panel count data. Simulation studies are carried out to demonstrate the numerical efficiency of the proposed algorithm compared to the existing methods in the literature. Some key words: Quadratic programming; Interval censored data; Isotonic Regression; Iterative convex minorant algorithm; Monte-Carlo.
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