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作者：Xu, Hongquan; Cheng, Ching-Shui
作者单位：University of California System; University of California Los Angeles; University of California System; University of California Berkeley
摘要：Chen and Cheng [Ann. Statist. 34 (2006) 546-558] discussed the method of doubling for constructing two-level fractional factorial designs. They showed that for 9N/32 <= n <= 5N/16, all minimum aberration designs with N runs and n factors are projections of the maximal design with 5N/16 factors which is constructed by repeatedly doubling the 2(5-1) design defined by I = ABCDE. This paper develops a general complementary design theory for doubling. For any design obtained by repeated doubling, g...
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作者：Sarkar, Sanat K.
作者单位：Pennsylvania Commonwealth System of Higher Education (PCSHE); Temple University
摘要：In a multiple testing problem where one is willing to tolerate a few false rejections, procedure controlling the familywise error rate (FWER) can potentially be improved in terms of its ability to detect false null hypotheses by generalizing it to control the k-FWER, the probability of falsely rejecting at least k null hypotheses, for some fixed k > 1. Simes' test for testing the intersection null hypothesis is generalized to control the k-FWER weakly, that is, under the intersection null hypo...
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作者：Lafferty, John; Wasserman, Larry
作者单位：Carnegie Mellon University; Carnegie Mellon University
摘要：We present a greedy method for simultaneously performing local bandwidth selection and variable selection in nonparametric regression. The method starts with a local linear estimator with large bandwidths, and incrementally decreases the bandwidth of variables for which the gradient of the estimator with respect to bandwidth is large. The method-called rodeo (regularization of derivative expectation operator)-conducts a sequence of hypothesis tests to threshold derivatives, and is easy to impl...
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作者：Yu, Kyusang; Park, Byeong U.; Mammen, Enno
作者单位：University of Mannheim; Seoul National University (SNU)
摘要：Generalized additive models have been popular among statisticians and data analysts in multivariate nonparametric regression with non-Gaussian responses including binary and count data. In this paper, a new likelihood approach for fitting generalized additive models is proposed. It aims to maximize a smoothed likelihood. The additive functions are estimated by solving a system of nonlinear integral equations. An iterative algorithm based on smooth backfitting is developed from the Newton-Kanto...
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作者：Radchenko, Peter
作者单位：University of Southern California
摘要：A general method is presented for deriving the limiting behavior of estimators that are defined as the values of parameters optimizing an empirical criterion function. The asymptotic behavior of such estimators is typically deduced from uniform limit theorems for rescaled and reparametrized criterion functions. The new method can handle cases where the standard approach does not yield the complete limiting behavior of the estimator. The asymptotic analysis depends on a decomposition of criteri...
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作者：Wu, Wei Biao
作者单位：University of Chicago
摘要：A popular framework for false discovery control is the random effects model in which the null hypotheses are assumed to be independent. This paper generalizes the random effects model to a conditional dependence model which allows dependence between null hypotheses. The dependence can be useful to characterize the spatial structure of the null hypotheses. Asymptotic properties of false discovery proportions and numbers of rejected hypotheses are explored and a large-sample distributional theor...
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作者：Ren, Jian-Jian
作者单位：State University System of Florida; University of Central Florida
摘要：In this article, the weighted empirical likelihood is applied to a general setting of two-sample semiparametric models, which includes biased sampling models and case-control logistic regression models as special cases. For various types of censored data, such as right censored data, doubly censored data, interval censored data and partly interval-censored data, the weighted empirical likelihood-based semiparametric maximum likelihood estimator ((theta) over tilde (n), (F) over tilde (n)) for ...
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作者：Li, Runze; Liang, Hua
作者单位：Pennsylvania Commonwealth System of Higher Education (PCSHE); Pennsylvania State University; Pennsylvania State University - University Park; Pennsylvania Commonwealth System of Higher Education (PCSHE); Pennsylvania State University; Pennsylvania State University - University Park; University of Rochester
摘要：In this paper, we are concerned with how to select significant variables in semiparametric modeling. Variable selection for semiparametric regression models consists of two components: model selection for nonparametric components and selection of significant variables for the parametric portion. Thus, semiparametric variable selection is much more challenging than parametric variable selection (e.g., linear and generalized linear models) because traditional variable selection procedures includ...
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作者：Bickel, Peter J.; Levina, Elizaveta
作者单位：University of California System; University of California Berkeley; University of Michigan System; University of Michigan
摘要：This paper considers estimating a covariance matrix of p variables from n observations by either banding or tapering the sample covariance matrix, or estimating a banded version of the inverse of the covariance. We show that these estimates are consistent in the operator norm as long as (log p)/n -> 0, and obtain explicit rates. The results are uniform over some fairly natural well-conditioned families of covariance matrices. We also introduce an analogue of the Gaussian white noise model and ...
