2004

最新文章

• The IOS test for model misspecification AI翻译
  作者：Presnell, B; Boos, DD
  作者单位：State University System of Florida; University of Florida; North Carolina State University
  摘要：A new test of model misspecification is proposed, based on the ratio of in-sample and out-of-sample likelihoods. The test is broadly applicable and, in simple problems, approximates well-known, intuitive methods. Using jackknife influence curve approximations, it is shown that the test statistic can be viewed asymptotically as a multiplicative contrast between two estimates of the information matrix, both of which are consistent under correct model specification. This approximation is used to ...
• Inconsistent estimation and asymptotically equal interpolations in model-based geostatistics AI翻译
  作者：Zhang, H
  作者单位：Washington State University
  摘要：it is shown that in model-based geostatistics, not all parameters in the Matern class can be estimated consistently if data are observed in an increasing density in a fixed domain, regardless of the estimation methods used. Nevertheless, one quantity can be estimated consistently by the maximum likelihood method, and this quantity is more important to spatial interpolation. The results are established by using the properties of equivalence and orthogonality of probability measures. Some suffic...
• Optimal experimental designs when some independent variables are not subject to control AI翻译
  作者：López-Fidalgo, J; Garcet-Rodríguez, SA
  作者单位：University of Salamanca
  摘要：This article considers the problem of constructing optimal designs for regression models when the design space is a product space and some of the variables are not under the control of the practitioner. A variable that is not tinder control can have known values before the experiment is performed or else unknown values before the experiment is realized. The first case is briefly discussed in the literature. The aim of this work is to provide equivalence theorems for the second case and the mix...
• Discrimination and classification of nonstationary time series using the SLEX model AI翻译
  作者：Huang, HY; Ombao, H; Stoffer, DS
  作者单位：Fu Jen Catholic University; University of Illinois System; University of Illinois Urbana-Champaign; Pennsylvania Commonwealth System of Higher Education (PCSHE); University of Pittsburgh
  摘要：Statistical discrimination for nonstationary random processes is important in many applications. Our goal was to develop a discriminant scheme that can extract local features of the time series, is consistent, and is computationally efficient. Here, we propose a discriminant scheme based on the SLEX (smooth localized complex exponential) library. The SLEX library forms a collection of Fourier-type bases that are simultaneously orthogonal and localized in both time and frequency domains. Thus, ...
• Cholesky residuals for assessing normal errors in a linear model with correlated outcomes AI翻译
  作者：Houseman, EA; Ryan, LM; Coull, BA
  作者单位：Harvard University; Harvard T.H. Chan School of Public Health
  摘要：Despite the widespread popularity of linear models for correlated outcomes (e.g., linear mixed models and time series models), distribution diagnostic methodology remains relatively underdeveloped in this context. In this article we present an easy-to-implement approach that lends itself to graphical displays of model fit. Our approach involves multiplying the estimated marginal residual vector by the Cholesky decomposition of the inverse of the estimated marginal variance matrix. The resultin...
• Improved semiparametric time series models of air pollution and mortality AI翻译
  作者：Dominici, F; McDermott, A; Hastie, TJ
  作者单位：Johns Hopkins University; Stanford University
  摘要：In 2002, methodological issues around time series analyses of air pollution and health attracted the attention of the scientific community, policy makers, the press, and the diverse stakeholders concerned with air pollution. As the U.S. Environmental Protection Agency (EPA) was finalizing its most recent review of epidemiologic evidence on particulate matter air pollution (PM), statisticians and epidemiologists found that the S-PLUS implementation of generalized additive models (GAMs) can over...
• Estimating the interest rate term structure of corporate debt with a semiparametric penalized spline model AI翻译
  作者：Jarrow, R; Ruppert, D; Yu, Y
  作者单位：Cornell University; University System of Ohio; University of Cincinnati; Cornell University
  摘要：This article provides a new methodology for estimating the term structure of corporate debt using a semiparametric penalized spline model. The method is applied to a case study of AT&T bonds. Typically, very few data are available on individual corporate bond prices, too little to find a nonparametric estimate of term structure from these bonds alone. This problem is solved by borrowing strength from Treasury bond data. More specifically, we combine a nonparametric model for the term structure...
• Nonlinear and nonparametric regression and instrumental variables AI翻译
  作者：Carroll, RJ; Ruppert, D; Crainiceanu, CM; Tosteson, TD; Karagas, MR
  作者单位：Texas A&M University System; Texas A&M University College Station; Cornell University; Johns Hopkins University; Dartmouth College
  摘要：We consider regression when the predictor is measured with error and an instrumental variable (TV) is available. The regression function., or nonparametrically. Our major new result shows that the regression function and all parameters in can be modeled linearly, nonlinearly the measurement error model are identified under relatively weak conditions, much weaker than previously known to imply identifiability. In addition, we exploit a characterization of the IV estimator as a classical correct...
• Calibrated probabilistic mesoscale weather field forecasting: The geostatistical output perturbation method AI翻译
  作者：Gel, Y; Raftery, AE; Gneiting, T
  作者单位：George Washington University; University of Washington; University of Washington Seattle
  摘要：Probabilistic weather forecasting consists of finding a joint probability distribution for future weather quantities or events. It is typically done by using a numerical weather prediction model, perturbing the inputs to the model in various ways, and running the model for each perturbed set of inputs. The result is then viewed as an ensemble of forecasts, taken to be a sample from the joint probability distribution of the future weather quantities of interest. This is typically not feasible f...
• Inference after model selection AI翻译
  作者：Shen, XT; Huang, HC; Ye, J
  作者单位：University of Minnesota System; University of Minnesota Twin Cities; City University of New York (CUNY) System; Baruch College (CUNY)
  摘要：Typical modeling strategies involve model selection, which has a significant effect on inference of estimated parameters. Common practice is to use a selected model ignoring uncertainty introduced by the process of model selection. This could yield overoptimistic inferences, resulting in false discovery. In this article we develop a general methodology via optimal approximation for estimating the mean and variance of complex statistics that involve the process of model selection. This allows u...