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作者：Hobert, JP; Altman, NS; Schofield, CL
作者单位：Cornell University; Cornell University
摘要：Legislation passed in 1990 reducing the allowable sulfur dioxide emission levels in the United States is expected to reduce acidity in the Adirondack region of New York State. The number of fish species in a lake (species richness) depends on a number of physical and chemical factors, including the area, elevation, and acidity of the lake. Data on these and other factors are available for 1,166 Adirondack lakes. The data are analyzed with the goal of quantifying the effects of acid deposition ...
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作者：Percival, DB; Mofjeld, HO
作者单位：University of Washington; University of Washington Seattle; National Oceanic Atmospheric Admin (NOAA) - USA; University of Washington; University of Washington Seattle
摘要：Subtidal coastal sea level fluctuations affect coastal ecosystems and the consequences of destructive events such as tsunamis. We analyze a time series of subtidal fluctuations at Crescent City, California, during 1980-1991 using the maximal overlap discrete wavelet transform (MODWT). Our analysis shows that the variability in these fluctuations depends on the season for scales of 32 days and less. We show how the MODWT characterizes nonstationary behavior succinctly and how this characterizat...
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作者：Linton, OB; Chen, R; Wang, NS; Hardle, W
作者单位：Yale University; Texas A&M University System; Texas A&M University College Station; Humboldt University of Berlin
摘要：We consider a nonparametric regression model with a parametric family of dependent variable transformations, one of which induces additive covariate effects. We estimate the additive regression effects using the integration method and estimate the transformation parameter from a profiled instrumental variable and pseudolikelihood criterion. The asymptotic distributions of the parameter and regression estimates are given. The practical performance is investigated via an application.
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作者：Jones, MC; Signorini, DF
作者单位：University of Edinburgh
摘要：We consider many kernel-based density estimators, all theoretically improving bias from O(h(2)), as the smoothing parameter h --> 0, to O(h(4)). Examples include higher-order kernels, variable kernel methods, and transformation and multiplicative bias-correction approaches. We stress the similarities between what appear to be disparate approaches. In particular, we show how the mean squared errors of all methods have the same form. Our main practical contribution is a comparative simulation st...
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作者：Sherman, M
摘要：We extend subseries methods for stationary sequences to the regression setting. To estimate sampling distributions, the subseries approach computes the statistic of interest on all possible subseries of a shorter length than the original series, and uses the distribution of these replicates to mimic the distribution of the original statistic. For proper choice of subseries length. the regression parameters can be estimated to order O(n(-2/3)), thus improving on the normal approximation. The re...
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作者：Peruggia, M
摘要：I consider a standard specification of the Bayesian linear model and derive necessary and sufficient conditions for the variance of the case-deletion importance sampling weights to be finite. The conditions have an intuitive interpretation in terms of familiar frequentist measures of leverage and influence and are easy to verify. I present two real data examples in which the necessary conditions fail to hold for some observations and the corresponding importance sampling estimates are highly u...
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作者：Banerjee, M; Frees, EW
作者单位：Wayne State University; University of Wisconsin System; University of Wisconsin Madison; University of Wisconsin System; University of Wisconsin Madison
摘要：Influence diagnostics are important for analyzing cross-sectional regression studies, because they allow the analyst to understand the impact of individual observations on the estimated regression model. In this article we consider the role of influence diagnostics in subject-specific longitudinal models. Diagnostics are proposed under both fixed and random subject effects. Our approach is based on subject deletion, which in this setting involves deleting a group of correlated observations. We...
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作者：Raftery, AE; Madigan, D; Hoeting, JA
作者单位：Colorado State University System; Colorado State University Fort Collins
摘要：We consider the problem of accounting for model uncertainty in linear regression models. Conditioning on a single selected model ignores model uncertainty, and thus leads to the underestimation of uncertainty when making inferences about quantities of interest. A Bayesian solution to this problem involves averaging over all possible models (i.e., combinations of predictors) when making inferences about quantities of interest. This approach is often not practical. In this article we offer two a...
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作者：Richardson, AM
摘要：Bounded influence estimation (also known as generalized M or GM estimation) in the regression model is reviewed. The definitions of bounded influence estimation proposed by Mallows and Schweppe are then extended to the mixed linear model. This is achieved by applying appropriate weight functions to maximum likelihood and restricted maximum likelihood estimating equations. The asymptotic properties of the new estimators are obtained, and the estimators are applied to an artificial dataset. The ...
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作者：DiCiccio, TJ; Kass, RE; Raftery, A; Wasserman, L
作者单位：Carnegie Mellon University; University of Washington; University of Washington Seattle
摘要：The Bayes factor is a ratio of two posterior normalizing constants. which may be difficult to compute. We compare several methods of estimating Bayes factors when it is possible to simulate observations from the posterior distributions, via Markov chain Monte Carlo or other techniques. The methods that we study are all easily applied without consideration of special features of the problem, provided that each posterior distribution is well behaved in the sense of having a single dominant mode....
