466期

最新文章

• Bayesian factor analysis for spatially correlated data, with application to summarizing area-level material deprivation from census data AI翻译
  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...
• Equivalence between conditional and mixture approaches to the Rasch model and matched case-control studies, with applications AI翻译
  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...
• A Bayesian insertion/deletion algorithm for distant protein motif searching via entropy filtering AI翻译
  作者：Xie, J; Li, KC; Bina, M
  作者单位：Purdue University System; Purdue University; University of California System; University of California Los Angeles; Purdue University System; Purdue University
  摘要：Bayesian models have been developed that find ungapped motifs in multiple protein sequences. In (his article. we extend the model to allow for deletions and insertions in motifs. Direct generalization of the ungapped algorithm, based on Gibbs sampling, proved unsuccessful because the configuration space became much larger. To alleviate the convergence difficulty, a two-stage procedure is introduced. At the first stage. we develop a method called entropy filtering, which quick]), searchs good s...
• A semiparametric basis for combining estimation problems under quadratic loss AI翻译
  作者：Judge, GG; Mittelhammer, RC
  作者单位：University of California System; University of California Berkeley; Washington State University
  摘要：When there is uncertainty concerning the appropriate statistical model-estimator to use in representing the data sampling process, we consider a basis for optimally combining estimation problems. The objective is to produce natural adaptive estimators that are free of subjective choices and tuning parameters. In the context of two competing multivariate linear statistical models-estimators, we demonstrate a semiparametric Stein-like (SPSL) estimator, (beta) over bar((alpha) over cap), that, un...
• Testing homogeneity in a mixture distribution via the L2 distance between competing models AI翻译
  作者：Charnigo, R; Sun, JY
  作者单位：University of Kentucky; University of Kentucky; University System of Ohio; Case Western Reserve University
  摘要：Ascertaining the number of components in a mixture distribution is an interesting and challenging problem for statisticians. Chen, Chen. and Kalbfleisch recently proposed a modified likelihood ratio test (MLRT), which is distribution-free and locally most powerful, asymptotically. In this article we present a new method for testing whether a finite mixture distribution is homogeneous. Our method, the D test, is based on the L-2 distance between a fitted homogeneous model and a fitted heterogen...
• Monte Carlo state-space likelihoods by weighted posterior kernel density estimation AI翻译
  作者：De Valpine, P
  作者单位：University of California System; University of California Berkeley
  摘要：Maximum likelihood estimation and likelihood ratio tests for nonlinear. non-Gaussian state-space models require numerical integration for likelihood calculations. Several methods, including Monte Carlo (MC) expectation maximization, MC likelihood ratios, direct MC integration. and particle filter likelihoods. are inefficient for the motivating problem of stage-structured population dynamics models in experimental settings. An MC kernel likelihood (MCKL) method is presented that estimates class...
• A conditionally distribution-free multivariate sign test for one-sided alternatives AI翻译
  作者：Larocque, D; Labarre, M
  作者单位：Universite de Montreal; HEC Montreal
  摘要：We consider the problem of testing the hypothesis that a multivariate location vector is in the positive orthant. A conditionally distribution-free sign test is proposed for this problem. This test is related to the Hodges test and can be motivated by the union-intersection principle. Moreover, it is valid under very mild assumptions. A characterization of the conditional null distribution of the test statistic is given. We provide a step-by-step procedure that can be used to perform the test ...