-
作者：Balabdaoui, Fadoua; Rufibach, Kaspar; Wellner, Jon A.
作者单位：Universite PSL; Universite Paris-Dauphine; University of Zurich; University of Washington; University of Washington Seattle; University of Gottingen
摘要：We find limiting distributions of the nonparametric maximum likelihood estimator (MLE) of a log-concave density, that is, a density of the form f(0) = exp phi(0) where phi(0) is a concave function on R. The pointwise limiting distributions depend on the second and third derivatives at 0 of H-k, the lower invelope of an integrated Brownian motion process minus a drift term depending on the number of vanishing derivatives of phi(0) = log f(0) at the point of interest. We also establish the limit...
-
作者：Paul, Debashis; Peng, Jie
作者单位：University of California System; University of California Davis
摘要：[it this paper we consider two closely related problems: estimation of eigenvalues and eigenfunctions of the covariance kernel of functional data based on (possibly) irregular measurements, and the problem of estimating the eigenvalues and eigenvectors of the covariance matrix for high-dimensional Gaussian vectors. In [A geometric approach to maximum likelihood estimation of covariance kernel from sparse irregular longitudinal data (2007)], a restricted maximum likelihood (REML) approach has b...
-
作者：Gorfine, Malka; Zucker, David M.; Hsu, Li
作者单位：Technion Israel Institute of Technology; Hebrew University of Jerusalem; Fred Hutchinson Cancer Center
摘要：In this work we deal with correlated failure time (age at onset) data arising from population-based, case-control studies, where case and control probands are selected by population-based sampling and all array of risk factor measures is collected for both cases and controls and their relatives. Parameters of interest are effects of risk factors on the failure time hazard function and within-family dependencies among failure times after adjusting for the risk factors. Due to the retrospective ...
-
作者：Vovk, Vladimir; Nouretdinov, Ilia; Gammerman, Alex
作者单位：University of London; Royal Holloway University London
摘要：We consider the on-line predictive version of the standard problem of linear regression; the goal is to predict each consecutive response given the corresponding explanatory variables and all the previous observations. The standard treatment of prediction in linear regression analysis has two drawbacks: (1) the classical prediction intervals guarantee that the probability of error is equal to the nominal significance level epsilon, but this property per se does not imply that the long-run freq...
-
作者：Sarkar, Sanat K.; Guo, Wenge
作者单位：Pennsylvania Commonwealth System of Higher Education (PCSHE); Temple University; National Institutes of Health (NIH) - USA; NIH National Institute of Environmental Health Sciences (NIEHS)
摘要：The concept of k-FWER has received much attention lately as an appropriate error rate for multiple testing when one seeks to control at least k false rejections, for some fixed k >= 1. A less conservative notion, the k-FDR, has been introduced very recently by Sarkar [Ann. Statist. 34 (2006) 394-415], generalizing the false discovery rate of Benjamini and Hochberg [J. Roy. Statist. Soc. Ser. B 57 (1995) 289-300]. In this article, we bring newer insight to the k-FDR considering a mixture model ...
-
作者：Cohen, Arthur; Sackrowitz, Harold B.; Xu, Minya
作者单位：Rutgers University System; Rutgers University New Brunswick; Peking University
摘要：The most popular multiple testing procedures are stepwise procedures based on P-values for individual test statistics. Included among these are the false discovery rate (FDR) controlling procedures of Benjamini-Hochberg [J. Roy. Statist. Soc. Ser B 57 (1995) 289-300] and their offsprings. Even for models that entail dependent data, P-values based on marginal distributions are used. Unlike such methods, the new method takes dependency into account at all stages. Furthermore, the P-value procedu...
-
作者：Hjort, Nils Lid; McKeague, Ian W.; Van Keilegom, Ingrid
作者单位：University of Oslo; Columbia University; Universite Catholique Louvain; Tilburg University
摘要：This article extends the scope of empirical likelihood methodology ill three directions: to allow for plug-in estimates Of nuisance parameters in estimating equations, slower than root n-rates of convergence, and settings in which there are a relatively large number of estimating equations compared to the sample size. Calibrating empirical likelihood confidence regions with plug-in is sometimes intractable due to the complexity of the asymptotics, so we introduce a bootstrap approximation that...
-
作者：Li, Bing; Dong, Yuexiao
作者单位：Pennsylvania Commonwealth System of Higher Education (PCSHE); Pennsylvania State University; Pennsylvania State University - University Park
摘要：Sufficient dimension reduction methods often require stringent conditions on the joint distribution of the predictor, or, when such conditions are not satisfied, rely on marginal transformation or reweighting to fulfill them approximately. For example, a typical dimension reduction method would require the predictor to have elliptical or even multivariate normal distribution. In this paper, we reformulate the commonly used dimension reduction methods, via the notion of central solution space, ...
-
作者：Spokoiny, Vladimir
作者单位：Leibniz Association; Weierstrass Institute for Applied Analysis & Stochastics; Humboldt University of Berlin
摘要：This paper offers a new approach to modeling and forecasting of nonstationary time series with applications to volatility modeling for financial data. The approach is based on the assumption of local homogeneity: for every time point, there exists a historical interval of homogeneity, in which the volatility parameter can be well approximated by a constant. The proposed procedure recovers this interval from the data using the local change point (LCP) analysis. Afterward, the estimate of the vo...
-
作者：Koltchinskii, Vladimir
作者单位：University System of Georgia; Georgia Institute of Technology
摘要：Let (X. Y) be a random couple in S x T with unknown distribution P and (X-1, Y-1),..., (X-n, Y-n,) be i.i.d. copies of (X, Y). Denote P-n the empirical distribution of (X-1, Y-1),..., (X-n, Y-n). Let h(1),..., h(N): S bar right arrow [-1, 1] be a dictionary that consists of N functions. For lambda is an element of R-N, denote f(lambda) := Sigma(N)(j=1) lambda(j)h(j). Let l: T x R bar right arrow R be a given loss function and suppose it is convex with respect to the second variable. Let (l cen...
