-
作者：Derkach, Andriy; Lawless, Jerald F.; Sun, Lei
作者单位：University of Toronto; University of Waterloo; University of Toronto
摘要：Response-dependent sampling is widely used in settings where certain variables are expensive to obtain. Estimation has been thoroughly investigated but recent applications have emphasized tests of association for expensive covariates and a response variable. We consider testing and provide easily implemented likelihood score tests for generalized linear models under a broad range of sampling plans. We show that when there are no additional covariates, the score statistics are identical for con...
-
作者：Li, Guodong; Guan, Bo; Li, Wai Keung; Yu, Philip L. H.
作者单位：University of Hong Kong
摘要：This paper extends the classical two-regime threshold autoregressive model by introducing hysteresis to its regime-switching structure, which leads to a new model: the hysteretic autoregressive model. The proposed model enjoys the piecewise linear structure of a threshold model but has a more flexible regime switching mechanism. A sufficient condition is given for geometric ergodicity. Conditional least squares estimation is discussed, and the asymptotic distributions of its estimators and inf...
-
作者：Yu, Y.; Wang, T.; Samworth, R. J.
作者单位：University of Cambridge
摘要：The Davis-Kahan theorem is used in the analysis of many statistical procedures to bound the distance between subspaces spanned by population eigenvectors and their sample versions. It relies on an eigenvalue separation condition between certain population and sample eigenvalues. We present a variant of this result that depends only on a population eigenvalue separation condition, making it more natural and convenient for direct application in statistical contexts, and provide an improvement in...
-
作者：Ro, Kwangil; Zou, Changliang; Wang, Zhaojun; Yin, Guosheng
作者单位：Nankai University; University of Hong Kong
摘要：Outlier detection is an integral component of statistical modelling and estimation. For high-dimensional data, classical methods based on the Mahalanobis distance are usually not applicable. We propose an outlier detection procedure that replaces the classical minimum covariance determinant estimator with a high-breakdown minimum diagonal product estimator. The cut-off value is obtained from the asymptotic distribution of the distance, which enables us to control the Type I error and deliver r...
-
作者：Wang, Qin; Yin, Xiangrong; Critchley, Frank
作者单位：Virginia Commonwealth University; University of Kentucky; Open University - UK
摘要：Sufficient dimension reduction is a useful tool for studying the dependence between a response and a multi-dimensional predictor. In this article, a new formulation is proposed that is based on the Hellinger integral of order two, introduced as a natural measure of the regression information contained in the predictor subspace. The response may be either continuous or discrete. We establish links between local and global central subspaces, and propose an efficient local estimation algorithm. S...
-
作者：Danaher, P.; Paul, D.; Wang, P.
作者单位：NanoString Technologies; University of California System; University of California Davis; Icahn School of Medicine at Mount Sinai
摘要：The use of high-throughput data to study the changing behaviour of biological pathways has focused mainly on examining the changes in the means of pathway genes. In this paper, we propose instead to test for changes in the co-regulated and unregulated variability of pathway genes. We assume that the eigenvalues of previously defined pathways capture biologically relevant quantities, and we develop a test for biologically meaningful changes in the eigenvalues between classes. This test reflects...
-
作者：Qin, Jing; Zhang, Han; Li, Pengfei; Albanes, Demetrius; Yu, Kai
作者单位：National Institutes of Health (NIH) - USA; NIH National Institute of Allergy & Infectious Diseases (NIAID); National Institutes of Health (NIH) - USA; NIH National Cancer Institute (NCI); NIH National Cancer Institute- Division of Cancer Epidemiology & Genetics; University of Waterloo
摘要：Public registration databases and large cohort studies provide vital information on disease prevalence at various levels of a risk factor. This auxiliary information can be helpful in conducting statistical inference in a new study. We aim to develop a statistical procedure that improves the efficiency of the logistic regression model for a case-control study by utilizing auxiliary information on covariate-specific disease prevalence via a series of unbiased estimating equations. We adopt empi...
-
作者：Beskos, A.; Dureau, J.; Kalogeropoulos, K.
作者单位：University of London; University College London; University of London; London School Economics & Political Science
摘要：We consider continuous-time diffusion models driven by fractional Brownian motion. Observations are assumed to possess a nontrivial likelihood given the latent path. Due to the non-Markovian and high-dimensional nature of the latent path, estimating posterior expectations is computationally challenging. We present a reparameterization framework based on the Davies and Harte method for sampling stationary Gaussian processes and use it to construct a Markov chain Monte Carlo algorithm that allow...
-
作者：Giannerini, Simone; Maasoumi, Esfandiar; Dagum, Estela Bee
作者单位：University of Bologna; Emory University
摘要：We propose tests for nonlinear serial dependence in time series under the null hypothesis of general linear dependence, in contrast to the more widely studied null hypothesis of independence. The approach is based on combining an entropy dependence metric, which possesses many desirable properties and is used as a test statistic, with a suitable extension of surrogate data methods, a class of Monte Carlo distribution-free tests for nonlinearity, and a smoothed sieve bootstrap scheme. We show h...
-
作者：Kurtek, Sebastian; Bharath, Karthik
作者单位：University System of Ohio; Ohio State University; University of Nottingham
摘要：We propose a geometric framework to assess sensitivity of Bayesian procedures to modelling assumptions based on the nonparametric Fisher-Rao metric. While the framework is general, the focus of this article is on assessing local and global robustness in Bayesian procedures with respect to perturbations of the likelihood and prior, and on the identification of influential observations. The approach is based on a square-root representation of densities, which enables analytical computation of ge...
