Journal of the American Statistical Association

最新文章

• A Sieve Semiparametric Maximum Likelihood Approach for Regression Analysis of Bivariate Interval-Censored Failure Time Data AI翻译
  作者：Zhou, Qingning; Hu, Tao; Sun, Jianguo
  作者单位：University of Missouri System; University of Missouri Columbia; Capital Normal University; Capital Normal University
  摘要：Interval-censored failure time data arise in a number of fields and many authors have discussed various issues related to their analysis. However, most of the existing methods are for univariate data and there exists only limited research on bivariate data, especially on regression analysis of bivariate interval-censored data. We present a class of semiparametric transformation models for the problem and for inference, a sieve maximum likelihood approach is developed. The model provides a grea...
• Shrinkage Estimation for Multivariate Hidden Markov Models AI翻译
  作者：Fiecas, Mark; Franke, Juergen; von Sachs, Rainer; Kamgaing, Joseph Tadjuidje
  作者单位：University of Warwick; University of Kaiserslautern; Universite Catholique Louvain
  摘要：Motivated from a changing market environment over time, we consider high-dimensional data such as financial returns, generated by a hidden Markov model that allows for switching between different regimes or states. To get more stable estimates of the covariance matrices of the different states, potentially driven by a number of observations that are small compared to the dimension, we modify the expectation-maximization (EM) algorithm so that it yields the shrinkage estimators for the covarian...
• Comment: Extending the Latent Position Model for Networks AI翻译
  作者：Raftery, Adrian E.
  作者单位：University of Washington; University of Washington Seattle
• Fully Nonparametric Regression for Bounded Data Using Dependent Bernstein Polynomials AI翻译
  作者：Barrientos, Andres F.; Jara, Alejandro; Quintana, Fernando A.
  作者单位：Duke University; Pontificia Universidad Catolica de Chile
  摘要：We propose a novel class of probability models for sets of predictor-dependent probability distributions with bounded domain. The proposal extends the DirichletBernstein prior for single density estimation, by using dependent stick-breaking processes. A general model class and two simplified versions are discussed in detail. Appealing theoretical properties such as continuity, association structure, marginal distribution, large support, and consistency of the posterior distribution are establi...
• Set-Based Tests for the Gene-Environment Interaction in Longitudinal Studies AI翻译
  作者：He, Zihuai; Zhang, Min; Lee, Seunggeun; Smith, Jennifer A.; Kardia, Sharon L. R.; Roux, V. Diez; Mukherjee, Bhramar
  作者单位：University of Michigan System; University of Michigan; University of Michigan System; University of Michigan; Drexel University
  摘要：We propose a generalized score type test for set-based inference for the gene-environment interaction with longitudinally measured quantitative traits. The test is robust to misspecification of within subject correlation structure and has enhanced power compared to existing alternatives. Unlike tests for marginal genetic association, set-based tests for the gene-environment interaction face the challenges of a potentially misspecified and high-dimensional main effect model under the null hypot...
• Nonparametric Estimation of the Leverage Effect: A Trade-Off Between Robustness and Efficiency AI翻译
  作者：Kalnina, Ilze; Xiu, Dacheng
  作者单位：Universite de Montreal; University of Chicago
  摘要：We consider two new approaches to nonparametric estimation of the leverage effect. The first approach uses stock prices alone. The second approach uses the data on stock prices as well as a certain volatility instrument, such as the Chicago Board Options Exchange (CBOE) volatility index (VIX) or the Black-Scholes implied volatility. The theoretical justification for the instrument-based estimator relies on a certain invariance property, which can be exploited when high-frequency data are avail...
• Conditional Spectral Analysis of Replicated Multiple Time Series With Application to Nocturnal Physiology AI翻译
  作者：Krafty, Robert T.; Rosen, Ori; Stoffer, David S.; Buysse, Daniel J.; Hall, Martica H.
  作者单位：Pennsylvania Commonwealth System of Higher Education (PCSHE); University of Pittsburgh; University of Texas System; University of Texas El Paso; Pennsylvania Commonwealth System of Higher Education (PCSHE); University of Pittsburgh; Pennsylvania Commonwealth System of Higher Education (PCSHE); University of Pittsburgh
  摘要：This article considers the problem of analyzing associations between power spectra of multiple time series and cross-sectional outcomes when data are observed from multiple subjects. The motivating application comes from sleep medicine, where researchers are able to noninvasively record physiological time series signals during sleep. The frequency patterns of these signals, which can be quantified through the power spectrum, contain interpretable information about biological processes. An impo...
• Bayesian Calibration of Inexact Computer Models AI翻译
  作者：Plumlee, Matthew
  作者单位：University of Michigan System; University of Michigan
  摘要：Bayesian calibration is used to study computer models in the presence of both a calibration parameter and model bias. The parameter in the predominant methodology is left undefined. This results in an issue, where the posterior of the parameter is suboptimally broad. There has been no generally accepted alternatives to date. This article proposes using Bayesian calibration, where the prior distribution on the bias is orthogonal to the gradient of the computer model. Problems associated with Ba...
• A Directional Mixed Effects Model for Compositional Expenditure Data AI翻译
  作者：Scealy, J. L.; Welsh, A. H.
  作者单位：Australian National University; Australian National University
  摘要：Compositional data are vectors of proportions defined on the unit simplex and this type of constrained data occur frequently in Government surveys. It is also possible for the compositional data to be correlated due to the clustering or grouping of the observations within small domains or areas. We propose a new class of the mixed model for compositional data based on the Kent distribution for directional data, where the random effects also have Kent distributions. One useful property of the n...
• Augmented Particle Filters AI翻译
  作者：Yun, Jonghyun; Yang, Fan; Chen, Yuguo
  作者单位：University of Texas System; University of Texas Arlington; University of Illinois System; University of Illinois Urbana-Champaign
  摘要：Particle filters have been widely used for online filtering problems in state-space models (SSMs). The current available proposal distributions depend either only on the state dynamics, or only on the observation, or on both sources of information but are not available for general SSMs. In this article, we develop a new particle filtering algorithm, called the augmented particle filter (APF), for online filtering problems in SSMs. The APF combines two sets of particles from the observation equ...