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近似非高斯贝叶斯估计与众数一致性
SUMMARY A new recursive estimation procedure is proposed for the location of a dynamic linear model with non-normal errors. The procedure is a modification of a modal approximation algorithm, which is shown to be prone to instabilities. The modification is motivated by a notion of posterior modal consistency.
生物医学时间序列的建模与监测
A framework for modeling and monitoring medical time series is developed, based on extensions to the linear dynamic model. The approach is designed to provide for on-line, recursive updating and inference for time series that are subject to several forms of potential discontinuous change, and that may have missing values. The models and methods introduced are illustrated with three biomedical series.
基于自回归先验的批次验收方案
In many batch sampling situations it is reasonable to assume that a correlation exists between the true mean qualities of successively produced batches. A model considered by Campling (1968) is here reanalyzed using the Bayesian linear model framework of Lindley & Smith (1972), and a wider class of serial sampling acceptance schemes derived and compared.
随机变量序列变点推断的贝叶斯方法
A Bayesian approach is considered to the problem of making inferences about the point in a sequence of random variables at which the underlying distribution changes. Inferences are based on the posterior probabilities of the possible change-points. Detailed analyses are given for cases in which the distributions are binomial and normal, and numerical illustrations are provided. An informal sequential procedure is also noted.