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最新文章

• Computational and inferential difficulties with mixture posterior distributions. AI翻译
  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...
• Statistical properties and uses of the wavelet variance estimator for the scale analysis of time series AI翻译
  作者：Serroukh, A; Walden, AT; Percival, CB
  作者单位：Imperial College London; University of Washington; University of Washington Seattle
  摘要：Many physical processes are an amalgam of components operating on different scales, and scientific questions about observed data are often inherently linked to understanding the behavior at different scales. We explore time-scale properties of time series through the variance at different scales derived using wavelet methods. The great advantage of wavelet methods over ad hoc modifications of existing techniques is that wavelets provide exact scale-based decomposition results. We consider proc...
• Spatial Poisson regression for health and exposure data measured at disparate resolutions AI翻译
  作者：Best, NG; Ickstadt, K; Wolpert, RL
  作者单位：Imperial College London; Duke University
  摘要：Ecological regression studies are widely used to examine relationships between disease rates for small geographical areas and exposure to environmental risk factors. The raw data for such studies, including disease cases, environmental pollution concentrations, and the reference population at risk, are typically measured at various levels of spatial aggregation but are accumulated to a common geographical scale to facilitate statistical analysis. In this traditional approach, heterogeneous exp...
• Nonparametric function estimation for clustered data when the predictor is measured without/with error AI翻译
  作者：Lin, XH; Carroll, RJ
  作者单位：University of Michigan System; University of Michigan; Texas A&M University System; Texas A&M University College Station; Texas A&M University System; Texas A&M University College Station
  摘要：We consider local polynomial kernel regression with a single covariate for clustered data using estimating equations. We assume that at most m < infinity observations are available on each cluster. In the case of random regressors. with no measurement error in the predictor, we show that it is generally the best strategy to ignore entirely the correlation structure within each cluster and instead pretend that all observations are independent. In the Further special case of longitudinal data on...
• Causal inference without counterfactuals - Comment AI翻译
  作者：Rubin, DB
  作者单位：Harvard University
• REACT scatterplot smoothers: Superefficiency through basis economy AI翻译
  作者：Beran, R
  作者单位：University of California System; University of California Berkeley
  摘要：REACT estimators for the mean of a linear model involve three steps: transforming the model to a canonical form that provides an economical representation of the unknown mean vector, estimating the risks of a class of candidate linear shrinkage estimators, and adaptively selecting the candidate estimator that minimizes estimated risk. Applied to one- or higher-way layouts, the REACT method generates automatic scatterplot smoothers that compete well on standard datasets with the best fits obtai...
• P values for composite null models AI翻译
  作者：Bayarri, MJ; Berger, JO
  作者单位：University of Valencia; Duke University
  摘要：The problem of investigating compatibility of an assumed model with the data is investigated in the situation when the assumed model has unknown parameters. The most frequently used measures of compatibility are p values, based on statistics T for which large values are deemed to indicate incompatibility of the data and the model. When the null model has unknown parameters. ?, values are not uniquely defined. The proposals for computing a p value in such a situation include the plug-in and sim...
• Estimating and using propensity scores with partially missing data AI翻译
  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...
• Causal analysis in the health sciences AI翻译
  作者：Greenland, S
  作者单位：University of California System; University of California Los Angeles
• Finance: A selective survey AI翻译
  作者：Lo, AW
  作者单位：Massachusetts Institute of Technology (MIT)