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作者：Tseng, Y. K.; Su, Y. R.; Mao, M.; Wang, J. L.
作者单位：National Central University; Fred Hutchinson Cancer Center; University of California System; University of California Davis
摘要：In clinical trials and other medical studies, it has become increasingly common to observe simultaneously an event time of interest and longitudinal covariates. In the literature, joint modelling approaches have been employed to analyse both survival and longitudinal processes and to investigate their association. However, these approaches focus mostly on developing adaptive and flexible longitudinal processes based on a prespecified survival model, most commonly the Cox proportional hazards m...
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作者：Xu, Peirong; Zhu, Ji; Zhu, Lixing; Li, Yi
作者单位：Southeast University - China; University of Michigan System; University of Michigan; Hong Kong Baptist University; University of Michigan System; University of Michigan
摘要：Linear discriminant analysis has been widely used to characterize or separate multiple classes via linear combinations of features. However, the high dimensionality of features from modern biological experiments defies traditional discriminant analysis techniques. Possible interfeature correlations present additional challenges and are often underused in modelling. In this paper, by incorporating possible interfeature correlations, we propose a covariance-enhanced discriminant analysis method ...
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作者：Zhao, Y. Q.; Zeng, D.; Laber, E. B.; Song, R.; Yuan, M.; Kosorok, M. R.
作者单位：University of Wisconsin System; University of Wisconsin Madison; University of North Carolina; University of North Carolina Chapel Hill; North Carolina State University; University of Wisconsin System; University of Wisconsin Madison
摘要：Individualized treatment rules recommend treatments based on individual patient characteristics in order to maximize clinical benefit. When the clinical outcome of interest is survival time, estimation is often complicated by censoring. We develop nonparametric methods for estimating an optimal individualized treatment rule in the presence of censored data. To adjust for censoring, we propose a doubly robust estimator which requires correct specification of either the censoring model or surviv...
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作者：Gervini, Daniel
作者单位：University of Wisconsin System; University of Wisconsin Milwaukee
摘要：A characteristic feature of functional data is the presence of phase variability in addition to amplitude variability. Existing functional regression methods do not handle time variability in an explicit and efficient way. In this paper we introduce a functional regression method that incorporates time warping as an intrinsic part of the model. The method achieves good predictive power in a parsimonious way and allows unified statistical inference about phase and amplitude components. The asym...
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作者：Genton, Marc G.; Padoan, Simone A.; Sang, Huiyan
作者单位：King Abdullah University of Science & Technology; Bocconi University; Texas A&M University System; Texas A&M University College Station
摘要：Max-stable processes allow the spatial dependence of extremes to be modelled and quantified, so they are widely adopted in applications. For a better understanding of extremes, it may be useful to study several variables simultaneously. To this end, we study the maxima of independent replicates of multivariate processes, both in the Gaussian and Student-t cases. We define a Poisson process construction and introduce multivariate versions of the Smith Gaussian extreme-value, the Schlather extre...
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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...
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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...
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作者：Kato, Shogo; Jones, M. C.
作者单位：Research Organization of Information & Systems (ROIS); Institute of Statistical Mathematics (ISM) - Japan; Open University - UK
摘要：This article presents a class of four-parameter distributions for circular data that are unimodal, possess simple characteristic and density functions and a tractable distribution function, can be interpretably parameterized directly in terms of their trigonometric moments, afford a very wide range of skewness and kurtosis, envelop numerous interesting submodels including the wrapped Cauchy and cardioid distributions, allow straightforward parameter estimation by both method of moments and max...
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作者：Chakraborty, Anirvan; Chaudhuri, Probal
作者单位：Indian Statistical Institute; Indian Statistical Institute Kolkata
摘要：The Wilcoxon-Mann-Whitney test is a robust competitor of the test in the univariate setting. For finite-dimensional multivariate non-Gaussian data, several extensions of the Wilcoxon-Mann-Whitney test have been shown to outperform Hotelling's test. In this paper, we study a Wilcoxon-Mann-Whitney-type test based on spatial ranks in infinite-dimensional spaces, we investigate its asymptotic properties and compare it with several existing tests. The proposed test is shown to be robust with respec...
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作者：Wu, Yuanshan; Yin, Guosheng
作者单位：Wuhan University; University of Hong Kong
摘要：To accommodate the heterogeneity that is often present in ultrahigh-dimensional data, we propose a conditional quantile screening method, which enables us to select features that contribute to the conditional quantile of the response given the covariates. The method can naturally handle censored data by incorporating a weighting scheme through redistribution of the mass to the right; moreover, it is invariant to monotone transformation of the response and requires substantially weaker conditio...
