-
作者：Chen, Xiaohong; Wu, Wei Biao; Yi, Yanping
作者单位：Yale University; University of Chicago; New York University
摘要：This paper considers the efficient estimation of copula-based semiparametric strictly stationary Markov models. These models are characterized by nonparametric invariant (one-dimensional marginal) distributions and parametric bivariate copula functions where the copulas capture temporal dependence and tail dependence of the processes. The Markov processes generated via tail dependent copulas may look highly persistent and are useful for financial and economic applications. We first show that M...
-
作者：Fan, Jianqing; Wu, Yichao; Feng, Yang
作者单位：Princeton University; North Carolina State University
摘要：Generalized linear models and the quasi-likelihood method extend the ordinary regression models to accommodate more general conditional distributions of the response. Nonparametric methods need no explicit parametric specification, and the resulting model is completely determined by the data themselves. However, nonparametric estimation schemes generally have a slower convergence rate such as the local polynomial smoothing estimation of nonparametric generalized linear models studied in Fan, H...
-
作者：Luo, Ronghua; Wang, Hansheng; Tsai, Chih-Ling
作者单位：Southwestern University of Finance & Economics - China; Peking University; University of California System; University of California Davis
摘要：In regression analysis, we employ contour projection (CP) to develop a new dimension reduction theory. Accordingly, we introduce the notions of the central contour subspace and generalized contour subspace. We show that both of their structural dimensions are no larger than that of the central subspace Cook [Regression Graphics (1998b) Wiley]. Furthermore, we employ CP-sliced inverse regression, CP-sliced average variance estimation and CP-directional regression to estimate the generalized con...
-
作者：Wang, Huixia Judy; Zhu, Zhongyi; Zhou, Jianhui
作者单位：North Carolina State University; University of Virginia; Fudan University
摘要：Semiparametric models are often considered for analyzing longitudinal data for a good balance between flexibility and parsimony. In this paper, we study a class of marginal partially linear quantile models with possibly varying coefficients. The functional coefficients are estimated by basis function approximations. The estimation procedure is easy to implement, and it requires no specification of the error distributions. The asymptotic properties of the proposed estimators are established for...
-
作者：Hall, Peter; Miller, Hugh
作者单位：University of Melbourne
摘要：The bootstrap is a popular and convenient method for quantifying the authority of an empirical ordering of attributes, for example of a ranking of the performance of institutions or of the influence of genes on a response variable. In the first of these examples, the number, p, of quantities being ordered is sometimes only moderate in sire; in the second it can be very large, often much greater than sample sire. However, we show that in both types of problem the conventional bootstrap can prod...
-
作者：Jung, Sungkyu; Marron, J. S.
作者单位：University of North Carolina; University of North Carolina Chapel Hill
摘要：Principal Component Analysis (PCA) is an important tool of dimension reduction especially when the dimension (or the number of variables) is very high. Asymptotic studies where the sample size is fixed, and the dimension grows [i.e., High Dimension, Low Sample Size (HDLSS)] are becoming increasingly relevant. We investigate the asymptotic behavior of the Principal Component (PC) directions. HDLSS asymptotics are used to study consistency, strong inconsistency and subspace consistency. We show ...
-
作者：Burman, Prabir; Shumway, Robert H.
作者单位：University of California System; University of California Davis
摘要：The focus of this paper is on trend estimation for a general state-space model Y-t = mu(t) + epsilon(t), where the dth difference of the trend {mu(t)} is assumed to be i.i.d., and the error sequence {epsilon(t)} is assumed to be a mean zero stationary process. A fairly precise asymptotic expression of the mean square error is derived for the estimator obtained by penalizing the dth order differences. Optimal rate of convergence is obtained, and it is shown to be asymptotically equivalent to a ...
-
作者：Chen, Xiaohong; Hansen, Lars Peter; Scheinkman, Jose
作者单位：Yale University; University of Chicago; Princeton University
摘要：We investigate a method for extracting nonlinear principal components (NPCs). These NPCs maximize variation subject to smoothness and orthogonality constraints; but we allow for a general class of constraints and multivariate probability densities, including densities without compact support and even densities with algebraic tails. We provide primitive sufficient conditions for the existence of these NPCs. By exploiting the theory of continuous-time, reversible Markov diffusion processes, we g...
-
作者：Bai, Zhidong; Jiang, Dandan; Yao, Jian-Feng; Zheng, Shurong
作者单位：Northeast Normal University - China; National University of Singapore; Northeast Normal University - China; Universite de Rennes; Universite de Rennes
摘要：In this paper, we give an explanation to the failure of two likelihood ratio procedures for testing about covariance matrices from Gaussian populations when the dimension p is large compared to the sample size n. Next, using recent central limit theorems for linear spectral statistics of sample covariance matrices and of random F-matrices, we propose necessary corrections for these LR tests to cope with high-dimensional effects. The asymptotic distributions of these corrected tests under the n...
-
作者：Brien, C. J.; Bailey, R. A.
作者单位：University of South Australia; University of London
摘要：One aspect of evaluating the design for an experiment is the discovery of the relationships between subspaces of the data space. Initially we establish the notation and methods for evaluating an experiment with a single randomization. Starting with two structures, or orthogonal decompositions of the data space, we describe how to combine them to form the overall decomposition for a single-randomization experiment that is structure balanced. The relationships between the two structures are char...
