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作者：Foster, DP; Stine, RA
作者单位：University of Pennsylvania
摘要：We predict the onset of personal bankruptcy using least squares regression. Although well publicized, only 2,244 bankruptcies occur in our dataset of 2.9 million months of credit-card activity. We use stepwise selection to find predictors of these from a mix of payment history. debt load. demographics, and their interactions. This combination of rare responses and over 67,000 possible predictors leads to a challenging modeling question: How does one separate coincidental from useful predictors...
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作者：Gelman, A
作者单位：Columbia University
摘要：Progress in statistical computation often leads to advances in statistical modeling. For example, it is surprisingly common that an existing model is reparameterized. solely, for computational purposes, but then this new configuration motivates a new family of models that is useful in applied statistics. One reason why this phenomenon may not have been noticed in statistics is that reparameterizations do not change the likelihood. In a Bayesian framework, however, a transformation of parameter...
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作者：Hogan, JW; Tchernis, R
作者单位：Brown University; Indiana University System; Indiana University Bloomington
摘要：This article describes a Bayesian hierarchical model for factor analysis of spatially correlated multivariate data. The first level specifies, for each area on a map, the distribution of a vector of manifest variables conditional on an underlying latent factor; at the second level, the area-specific latent factors have a joint distribution that incorporates spatial correlation. The framework allows for both marginal and conditional (e.g., conditional autoregressive) specifications of spatial c...
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作者：Ekström, M; Luna, SSD
作者单位：Umea University; Umea University
摘要：Subsampling and block resampling methods have been suggested in the literature to nonparametrically estimate the variance of statistics computed from spatial data. Usually stationary data are required. However, in empirical applications, the assumption of stationarity often must be rejected. This article proposes nonparametric methods to estimate the variance of (functions of) sample means based on nonstationary spatial data using subsampling. We assume that data are observed on a lattice in s...
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作者：Sardy, S; Tseng, P
作者单位：Swiss Federal Institutes of Technology Domain; Ecole Polytechnique Federale de Lausanne; University of Washington; University of Washington Seattle
摘要：We consider Bayesian nonpararnetric function estimation using a Markov random field prior based on the Laplace distribution. We describe efficient methods for finding the exact maximum a posteriori estimate, which handle constraints naturally and avoid the problems posed by nondifferentiability of the posterior distribution; the methods also make links to spline and wavelet smoothers and to a dual posterior distribution. Three automatic smoothing parameter selection procedures are described: e...
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作者：Ten Have, TR; Elliott, MR; Joffe, M; Zanutto, E; Datto, C
作者单位：University of Pennsylvania; University of Pennsylvania; University of Pennsylvania
摘要：This article addresses unique causal issues in the context of a randomized study on improving adherence to best practice guidelines by primary care physicians (PCP's) in treating their depressed patients. The study assessed an encouragement strategy to improve PCP guideline adherence. In this context. we compare two causal approaches: the conditional-compliance (CC) Bayesian latent class and the conditional-observable (CO) structural mean model methods. The CC methods estimate contrasts betwee...
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作者：Rice, KM
作者单位：MRC Biostatistics Unit
摘要：Analyses of data using Rasch models. including the special case of matched case-control studies, are common applications of conditional likelihood in which the usual inferential procedures are applied only after conditioning on an approximately ancillary statistic. Another common approach to the analysis of Rasch models is to integrate the nuisance parameters over a mixing distribution, using the marginal likelihood obtained as the basis for inference. We show that the full conditional likelih...
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作者：Bekele, BN; Thall, PF
作者单位：University of Texas System; UTMD Anderson Cancer Center
摘要：The scientific goal of a phase I oncology trial of a new chemotherapeutic agent is to find a dose with an acceptable level of toxicity. For ethical reasons, dose-finding is done adaptively, with doses chosen for successive cohorts of patients based on the data obtained from previous cohorts. Typically. patients are at risk for several qualitatively different toxicities, each occurring at several possible severity levels. In this article, we describe how we addressed the dose-finding problem in...
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作者：Choudhuri, N; Ghosal, S; Roy, A
作者单位：University System of Ohio; Case Western Reserve University; North Carolina State University; University System of Maryland; University of Maryland Baltimore County
摘要：This article describes a Bayesian approach to estimating the spectral density of a stationary time series. A nonparametric prior on the spectral density is described through Bernstein polynomials. Because the actual likelihood is very complicated, a pseudoposterior distribution is obtained by updating the prior using the Whittle likelihood. A Markov chain Monte Carlo algorithm for sampling front this posterior distribution is described that is used for computing the posterior mean, variance, a...
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作者：Ke, CL; Wang, YD
作者单位：University of California System; University of California Santa Barbara
摘要：Almost all of the current nonparametric regression methods, such as smoothing splines, generalized additive models, and varying-coefficients models, assume a linear relationship when nonparametric functions are regarded as parameters. In this article we propose a general class of smoothing spline nonlinear nonparametric models that allow nonparametric functions to act nonlinearly. They arise in many fields as either theoretical or empirical models. Our new estimation methods are based on an ex...
