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作者：ZHAO, LP
摘要：Studies in genetic epidemiology are generally required to collect phenotypes on subjects from human pedigrees that consist of blood relatives and their spouses. One of the main objectives in analyzing pedigree data is to study the segregation of underlying genes that may predispose certain phenotypes and thus cause phenotypic aggregation within pedigrees. Most classical segregation methods are maximum likelihood-based under highly specified distributional assumptions for phenotypes given under...
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作者：POLSON, NG; ROBERTS, GO
作者单位：University of Cambridge
摘要：We present an approach to model selection for a time series of data on a fine time scale. The underlying process generating the data is modelled as a continuous time stochastic process. The underlying continuous processes are assumed to be diffusions with time varying drift and diffusion coefficient. Several approaches to modelling the diffusion coefficient are described. To perform model selection, we propose an approximation to the Bayes factor that uses only the discrete data. We illustrate...
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作者：SMITH, RL
摘要：In an earlier paper, the author has studied asymptotic properties of maximum likelihood estimates for a class of nonregular models in which the range of the distribution depends on unknown parameters. Examples include Weibull and extreme value distributions. The present paper is concerned with the extension of this theory to the case when covariates are present. The proposed solution involves solving a linear programming problem for the regression parameters, followed by maximisation of a pseu...
