Journal of the American Statistical Association

最新文章

• Optimal Detection of Changepoints With a Linear Computational Cost AI翻译
  作者：Killick, R.; Fearnhead, P.; Eckley, I. A.
  作者单位：Lancaster University
  摘要：In this article, we consider the problem of detecting multiple changepoints in large datasets. Our focus is on applications where the number of changepoints will increase as we collect more data: for example, in genetics as we analyze larger regions of the genome, or in finance as we observe time series over longer periods. We consider the common approach of detecting changepoints through minimizing a cost function over possible numbers and locations of changepoints. This includes several esta...
• Positive-Definite l1-Penalized Estimation of Large Covariance Matrices AI翻译
  作者：Xue, Lingzhou; Ma, Shiqian; Zou, Hui
  作者单位：Princeton University; Chinese University of Hong Kong; University of Minnesota System; University of Minnesota Twin Cities
  摘要：The thresholding covariance estimator has nice asymptotic properties for estimating sparse large covariance matrices, but it often has negative eigenvalues when used in real data analysis. To fix this drawback of thresholding estimation, we develop a positive-definite l(1)-penalized covariance estimator for estimating sparse large covariance matrices. We derive an efficient alternating direction method to solve the challenging optimization problem and establish its convergence properties. Unde...
• Information Ratio Test for Model Misspecification in Quasi-Likelihood Inference AI翻译
  作者：Zhou, Qian M.; Song, Peter X. -K.; Thompson, Mary E.
  作者单位：Harvard University; Harvard T.H. Chan School of Public Health; University of Michigan System; University of Michigan; University of Waterloo
  摘要：In this article, we focus on the circumstances in quasi-likelihood inference that the estimation accuracy of mean structure parameters is guaranteed by correct specification of the first moment, but the estimation efficiency could be diminished due to misspecification of the second moment. We propose an information ratio (IR) statistic to test for model misspecification of the variance/covariance structure through a comparison between two forms of information matrix: the negative sensitivity m...
• A Multiscale Community Blockmodel for Network Exploration AI翻译
  作者：Ho, Qirong; Parikh, Ankur P.; Xing, Eric P.
  作者单位：Carnegie Mellon University
  摘要：Real-world networks exhibit a complex set of phenomena such as underlying hierarchical organization, multiscale interaction, and varying topologies of communities. Most existing methods do not adequately capture the intrinsic interplay among such phenomena. We propose a nonparametric multiscale community blockmodel (MSCB) to model the generation of hierarchies in social communities, selective membership of actors to subsets of these communities, and the resultant networks due to within- and cr...
• Inverse Realized Laplace Transforms for Nonparametric Volatility Density Estimation in Jump-Diffusions AI翻译
  作者：Todorov, Viktor; Tauchen, George
  作者单位：Northwestern University; Duke University
  摘要：This article develops a nonparametric estimator of the stochastic volatility density of a discretely observed Ito semimartingale in the setting of an increasing time span and finer mesh of the observation grid. There are two basic steps involved. The first step is aggregating the high-frequency increments into the realized Laplace transform, which is a robust nonparametric estimate of the underlying volatility Laplace transform. The second step is using a regularized kernel to invert the reali...
• Vast Volatility Matrix Estimation Using High-Frequency Data for Portfolio Selection AI翻译
  作者：Fan, Jianqing; Li, Yingying; Yu, Ke
  作者单位：Princeton University; Hong Kong University of Science & Technology
  摘要：Portfolio allocation with gross-exposure constraint is an effective method to increase the efficiency and stability of portfolios selection among a vast pool of assets, as demonstrated by Fan, Zhang, and Yu. The required high-dimensional volatility matrix can be estimated by using high-frequency financial data. This enables us to better adapt to the local volatilities and local correlations among a vast number of assets and to increase significantly the sample size for estimating the volatilit...
• Bayesian Inference for Dynamic Treatment Regimes: Mobility, Equity, and Efficiency in Student Tracking AI翻译
  作者：Zajonc, Tristan
  作者单位：Harvard University
  摘要：Policies in health, education, and economics often unfold sequentially and adapt to changing conditions. Such time-varying treatments pose problems for standard program evaluation methods because intermediate outcomes are simultaneously pretreatment confounders and posttreatment outcomes. This article extends the Bayesian perspective on causal inference and optimal treatment to these types of dynamic treatment regimes. A unifying idea remains ignorable treatment assignment, which now sequentia...
• Mixed Effects Designs: The Symmetry Assumption and Missing Data AI翻译
  作者：Gaugler, Trent; Akritas, Michael G.
  作者单位：Pennsylvania Commonwealth System of Higher Education (PCSHE); Pennsylvania State University; Pennsylvania State University - University Park
  摘要：The classical F test for the hypothesis of no main fixed effects in the two-way crossed mixed effects design is derived under model assumptions that include normality, variance homogeneity, and symmetry. The symmetry assumption specifies that the random main and interaction effects are independent. While it is known that the F test is robust against violations of the normality assumption and/or the homoscedasticity assumption in the balanced case, the effects of the symmetry assumption have no...
• Identifying the Effects of SNAP (Food Stamps) on Child Health Outcomes When Participation Is Endogenous and Misreported AI翻译
  作者：Kreider, Brent; Pepper, John V.; Gundersen, Craig; Jolliffe, Dean
  作者单位：Iowa State University; University of Virginia; University of Illinois System; University of Illinois Urbana-Champaign; The World Bank
  摘要：The literature assessing the efficacy of the Supplemental Nutrition Assistance Program (SNAP), formerly known as the Food Stamp Program, has long puzzled over positive associations between SNAP receipt and various undesirable health outcomes such as food insecurity. Assessing the causal impacts of SNAP, however, is hampered by two key identification problems: endogenous selection into participation and extensive systematic underreporting of participation status. Using data from the National He...
• Likelihood-Based EWMA Charts for Monitoring Poisson Count Data With Time-Varying Sample Sizes AI翻译
  作者：Zhou, Qin; Zou, Changliang; Wang, Zhaojun; Jiang, Wei
  作者单位：Jiangsu Normal University; Nankai University; Nankai University; Shanghai Jiao Tong University
  摘要：Many applications involve monitoring incidence rates of the Poisson distribution when the sample size varies over time. Recently, a couple of cumulative sum and exponentially weighted moving average (EWMA) control charts have been proposed to tackle this problem by taking the varying sample size into consideration. However, we argue that some of these charts, which perform quite well in terms of average run length (ARL), may not be appealing in practice because they have rather unsatisfactory ...