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作者：Kim, JT
摘要：The classical problem of assessing the goodness of tit of a postulated parametric distribution is investigated using techniques from nonparametric density estimation. A new test is proposed based on the data-selected order of a Fourier series density estimator. This test has the novel feature of providing an associated nonparametric estimator that can be used to estimate the unknown density when the null hypothesis is rejected. The limiting null distribution of the proposed test statistic is d...
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作者：Celeux, G; Hurn, M; Robert, CP
作者单位：University of Bath; Institut Polytechnique de Paris; ENSAE Paris
摘要：This article dears with both exploration and interpretation problems related to posterior distributions for mixture models. The specification of mixture posterior distributions means that the presence of Ic! modes is known immediately. Standard Markov chain Monte Carlo (MCMC) techniques usually have difficulties with well-separated modes such as occur here; the MCMC sampler stays within a neighborhood of a local mode and fails to visit other equally important modes. We show that exploration of...
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作者：D'Agostino, RB Jr; Rubin, DB
作者单位：Wake Forest University; Wake Forest Baptist Medical Center; Harvard University
摘要：Investigators in observational studies have no control over treatment assignment. As a result, large differences can exist between the treatment and control groups on observed covariates, which can lead to badly biased estimates of treatment effects. Propensity score methods are an increasingly popular method for balancing the distribution of the covariates in the two groups to reduce this bias; for example, using matching or subclassification, sometimes in combination with model-based adjustm...
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作者：Shen, XT
作者单位：University System of Ohio; Ohio State University
摘要：In survival analysis, a linear model often provides an adequate approximation after a suitable transformation of the survival times and possibly of the covariates. This article proposes a semiparametric regression method for estimating the regression parameter in the linear model without specifying the distribution of the random error, where the response variable is subject to so-called case 1 interval censoring. The method uses a constructed random-sieve likelihood and constraints, combining ...
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作者：Higdon, D
作者单位：Duke University
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作者：Nychka, D
作者单位：National Center Atmospheric Research (NCAR) - USA
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作者：Rissanen, J; Yu, B
作者单位：University of California System; University of California Berkeley
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作者：Vere-Jones, D
作者单位：Victoria University Wellington
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作者：Gunter, B; Holder, D
作者单位：Merck & Company; Merck & Company
