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作者：Dryden, Ian L.; Kume, Alfred; Le, Huiling; Wood, Andrew T. A.
作者单位：University of Nottingham; University of Kent
摘要：We propose an alternative to Kendall's shape space for reflection shapes of configurations in Rm with k labelled vertices, where reflection shape consists of all the geometric information that is invariant under compositions of similarity and reflection transformations. The proposed approach embeds the space of such shapes into the space P( k - 1) of ( k - 1) x ( k - 1) real symmetric positive semidefinite matrices, which is the closure of an open subset of a Euclidean space, and defines mean ...
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作者：Dunson, David B.; Peddada, Shyamal D.
作者单位：Duke University; National Institutes of Health (NIH) - USA; NIH National Institute of Environmental Health Sciences (NIEHS)
摘要：We consider Bayesian inference about collections of unknown distributions subject to a partial stochastic ordering. To address problems in testing of equalities between groups and estimation of group-specific distributions, we propose classes of restricted dependent Dirichlet process priors. These priors have full support in the space of stochastically ordered distributions, and can be used for collections of unknown mixture distributions to obtain a flexible class of mixture models. Theoretic...
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作者：Kuang, D.; Nielsen, B.; Nielsen, J. P.
作者单位：University of Oxford; University of Oxford; City St Georges, University of London
摘要：We consider forecasting from age-period-cohort models, as well as from the extended chain-ladder model. The parameters of these models are known only to be identified up to linear trends. Forecasts from such models may therefore depend on arbitrary linear trends. A condition for invariant forecasts is proposed. A number of standard forecast models are analysed.
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作者：Li, Yi; Prentice, Ross L.; Lin, Xihong
作者单位：Harvard University; University of Washington; University of Washington Seattle; Fred Hutchinson Cancer Center; Harvard University; Harvard T.H. Chan School of Public Health
摘要：We consider a class of semiparametric normal transformation models for right-censored bivariate failure times. Nonparametric hazard rate models are transformed to a standard normal model and a joint normal distribution is assumed for the bivariate vector of transformed variates. A semiparametric maximum likelihood estimation procedure is developed for estimating the marginal survival distribution and the pairwise correlation parameters. This produces an efficient estimator of the correlation p...
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作者：Oakes, David
作者单位：University of Rochester
摘要：Necessary and sufficient conditions for consistency of a simple estimator of Kendall's tau under bivariate censoring are presented. The results are extended to data subject to bivariate left truncation as well as right censoring.
