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作者：Zheng, Cheng; Zhou, Xiao-Hua
作者单位：University of Washington; University of Washington Seattle; US Department of Veterans Affairs; Veterans Health Administration (VHA); Vet Affairs Puget Sound Health Care System
摘要：Mediation analysis is an important tool in social and medical sciences as it helps to understand why an intervention works. The commonly used approach, given by Baron and Kenny, requires the strong assumption sequential ignorability' to yield causal interpretation. Ten Have and his colleagues proposed a rank preserving model to relax this assumption. However, the rank preserving model is restricted to the case with binary intervention and single mediator and needs another strong assumption ran...
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作者：Efron, Bradley
作者单位：Stanford University
摘要：In the absence of relevant prior experience, popular Bayesian estimation techniques usually begin with some form of uninformative' prior distribution intended to have minimal inferential influence. The Bayes rule will still produce nice looking estimates and credible intervals, but these lack the logical force that is attached to experience-based priors and require further justification. The paper concerns the frequentist assessment of Bayes estimates. A simple formula is shown to give the fre...
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作者：Schweinberger, Michael; Handcock, Mark S.
作者单位：Rice University; University of California System; University of California Los Angeles
摘要：Dependent phenomena, such as relational, spatial and temporal phenomena, tend to be characterized by local dependence in the sense that units which are close in a well-defined sense are dependent. In contrast with spatial and temporal phenomena, though, relational phenomena tend to lack a natural neighbourhood structure in the sense that it is unknown which units are close and thus dependent. Owing to the challenge of characterizing local dependence and constructing random graph models with lo...
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作者：Guan, Yongtao; Jalilian, Abdollah; Waagepetersen, Rasmus
作者单位：University of Miami; Razi University; Aalborg University
摘要：Fitting regression models for intensity functions of spatial point processes is of great interest in ecological and epidemiological studies of association between spatially referenced events and geographical or environmental covariates. When Cox or cluster process models are used to accommodate clustering that is not accounted for by the available covariates, likelihoodbased inference becomes computationally cumbersome owing to the complicated nature of the likelihood function and the associat...
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作者：Dutta, Somak; Mondal, Debashis
作者单位：University of Chicago; Oregon State University
摘要：We consider sparse spatial mixed linear models, particularly those described by Besag and Higdon, and develop an h-likelihood method for their statistical inference. The method proposed allows for singular precision matrices, as it produces estimates that coincide with those from the residual maximum likelihood based on appropriate differencing of the data and has a novel approach to estimating precision parameters by a gamma linear model. Furthermore, we generalize the h-likelihood method to ...
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作者：Gerber, Mathieu; Chopin, Nicolas
作者单位：University of Lausanne; Institut Polytechnique de Paris; ENSAE Paris; Institut Polytechnique de Paris; ENSAE Paris
摘要：We derive and study sequential quasi Monte Carlo (SQMC), a class of algorithms obtained by introducing QMC point sets in particle filtering. SQMC is related to, and may be seen as an extension of, the array-RQMC algorithm of L'Ecuyer and his colleagues. The complexity of SQMC is O{Nlog(N)}, where N is the number of simulations at each iteration, and its error rate is smaller than the Monte Carlo rate OP(N-1/2). The only requirement to implement SQMC algorithms is the ability to write the simul...
