Journal of the American Statistical Association

最新文章

• Approximate Methods for State-Space Models AI翻译
  作者：Koyama, Shinsuke; Perez-Bolde, Lucia Castellanos; Shalizi, Cosma Rohilla; Kass, Robert E.
  作者单位：Carnegie Mellon University; Carnegie Mellon University; Pennsylvania Commonwealth System of Higher Education (PCSHE); University of Pittsburgh; The Santa Fe Institute
  摘要：State-space models provide an important body of techniques for analyzing time series. but their use requires estimating Unobserved states The optimal estimate of the state Is its conditional expectation given the observation histories. and computing this expectation is hard when there are nonlinearities Existing filtering methods, including sequential Monte Carlo. tend to be either inaccurate or slow In this paper, we study a nonlinear filter for nonlinear/non-Gaussian state-space models. whic...
• A Statistical Framework for Differential Privacy AI翻译
  作者：Wasserman, Larry; Zhou, Shuheng
  作者单位：Carnegie Mellon University; Carnegie Mellon University; Swiss Federal Institutes of Technology Domain; ETH Zurich
  摘要：One goal of statistical privacy research construct a data release mechanism that protects individual privacy while preset ving information content An example is a random mechanism that takes an input database X and outputs a random database Z according to a distribution Q(n) (vertical bar X) Differential privacy is a particular privacy requirement developed by computer scientists in which Q (vertical bar X) IS required to be insensitive to changes in one data point in X This makes it difficult...
• Autoregressive Mixture Models for Dynamic Spatial Poisson Processes: Application to Tracking Intensity of Violent Crime AI翻译
  作者：Taddy, Matthew A.
  作者单位：University of Chicago
  摘要：This article develops a set of tools for smoothing and prediction with dependent point event patterns. The methodology is motivated by the problem of tracking weekly maps of violent crime events, but is designed to be straightforward to adapt to a wide variety of alternative settings. In particular, a Bayesian semiparametric framework is introduced for modeling correlated time series of marked spatial Poisson processes. The likelihood is factored into two independent components: the set of tot...
• The Value of Multiproxy Reconstruction of Past Climate AI翻译
  作者：Li, Bo; Nychka, Douglas W.; Ammann, Caspar M.
  作者单位：Purdue University System; Purdue University; National Center Atmospheric Research (NCAR) - USA
  摘要：Understanding the dynamics of climate change in its full richness requires the knowledge of long temperature time series. Although long-term, widely distributed temperature observations are not available, there are other forms of data, known as climate proxies, that can have a statistical relationship with temperatures and have been used to infer temperatures in the past before direct measurements. We propose a Bayesian hierarchical model to reconstruct past temperatures that integrates inform...
• Variable Selection With the Strong Heredity Constraint and Its Oracle Property AI翻译
  作者：Choi, Nam Hee; Li, William; Zhu, Ji
  作者单位：University of Michigan System; University of Michigan; University of Minnesota System; University of Minnesota Twin Cities
  摘要：In this paper. we extend the LASSO method (Tibshittant 1996) for simultaneously fitting a regression model and identifying important interaction terms Unlike most of the existing variable selection methods. our method automatically enforces the heredity constraint that in Interaction term can be included in the model only it the corresponding main terms are also included in the model Furthermore, we extend our method to generalized linear models, and show that It performs as well as if the tru...
• Indirect Cross-Validation for Density Estimation AI翻译
  作者：Savchuk, Olga Y.; Hart, Jeffrey D.; Sheather, Simon J.
  作者单位：State University of New York (SUNY) System; Binghamton University, SUNY; Texas A&M University System; Texas A&M University College Station
  摘要：A new method of bandwidth selection or kernel density estimators is proposed The method termed indirect cross-validation (ICY). makes use of so-called selection kernels Least-squares cross-validation (LSCV) is used to select the bandwidth of a selection-kernel estimator and this bandwidth is appropriately escaled for use in a Gaussian kernel estimator The proposed selection kernels are linear combinations of two Gaussian kennels and need not be unimodal or positive A theory is developed showin...
• Probabilistic Weather Forecasting for Winter Road Maintenance AI翻译
  作者：Berrocal, Veronica J.; Raftery, Adrian E.; Gneiting, Tilmann; Steed, Richard C.
  作者单位：University of Washington; University of Washington Seattle; Ruprecht Karls University Heidelberg; University of Washington; University of Washington Seattle
  摘要：Winter road maintenance is one of the main tasks for the Washington State Department of Transportation. Anti-icing, that is, the preemptive application of chemicals, is often used to keep the roadways free of ice. Given the preventive nature of anti-icing, accurate predictions of road ice are needed. Currently, anti-icing decisions are usually based on deterministic weather forecasts. However, the costs of the two kinds of errors are highly asymmetric because the cost of a road closure due to ...
• Dimension Reduction and Adaptation in Conditional Density Estimation AI翻译
  作者：Efromovich, Sam
  作者单位：University of Texas System; University of Texas Dallas
  摘要：An orthogonal series estimator of the conditional density of a response given a vector of continuous and ordinal/nominal categorical predictors is suggested. The estimator is based on writing a conditional density as a sum of orthogonal projections on all possible subspaces of reduced dimensionality and then estimating each projection via a shrinkage procedure. The shrinkage procedure uses a universal thresholding and a dyadic-blockwise shrinkage for low and high frequencies, respectively. The...
• Posterior Simulation in Countable Mixture Models for Large Datasets AI翻译
  作者：Guha, Subharup
  作者单位：University of Missouri System; University of Missouri Columbia
  摘要：Mixture models, or convex combinations of a countable number of probability distributions, offer an elegant framework for inference when the population of interest can be subdivided into latent clusters having random characteristics that are heterogeneous between, but homogeneous within, the clusters. Traditionally, the different kinds of mixture models have been motivated and analyzed from very different perspectives, and their common characteristics have not been fully appreciated. The infer...
• Test of Association Between Two Ordinal Variables While Adjusting for Covariates AI翻译
  作者：Li, Chun; Shepherd, Bryan E.
  作者单位：Vanderbilt University
  摘要：We propose a new set of test statistics to examine the association between two ordinal categorical variables X and Y after adjusting for continuous and/or categorical covariates Z. Our approach first fits multinomial (e.g.. proportional odds) models of X and Y, separately, on Z. For each subject, we then compute the conditional distributions of X and Y given Z. If there is no relationship between X and Y after adjusting for Z. then these conditional distributions will be independent, and the o...