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作者：Carlier, Guillaume; Chernozhukov, Victor; Galichon, Alfred
作者单位：Universite PSL; Universite Paris-Dauphine; Massachusetts Institute of Technology (MIT); Massachusetts Institute of Technology (MIT); New York University; New York University
摘要：We propose a notion of conditional vector quantile function and a vector quantile regression. A conditional vector quantile function (CVQF) of a random vector Y, taking values in R-d given covariates Z = z, taking values in R-k, is a map u bar right arrow Q(Y vertical bar Z) (u, z), which is monotone, in the sense of being a gradient of a convex function, and such that given that vector U follows a reference non-atomic distribution F-U, for instance uniform distribution on a unit cube in Rd, t...
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作者：Lee, Jason D.; Sun, Dennis L.; Sun, Yuekai; Taylor, Jonathan E.
作者单位：University of California System; University of California Berkeley; California State University System; California Polytechnic State University San Luis Obispo; University of California System; University of California Berkeley; Stanford University
摘要：We develop a general approach to valid inference after model selection. At the core of our framework is a result that characterizes. the distribution of a post-selection estimator conditioned on the selection event. We specialize the approach to model selection by the lasso to form valid confidence intervals for the selected coefficients and test whether all relevant variables have been included in the model.
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作者：Qiao, Wanli; Polonik, Wolfgang
作者单位：University of California System; University of California Davis
摘要：This paper provides a rigorous study of the nonparametric estimation of filaments or ridge lines of a probability density f. Points on the filament are considered as local extrema of the density when traversing the support of f along the integral curve driven by the vector field of second eigenvectors of the Hessian of f. We parametrize points on the filaments by such integral curves, and thus both the estimation of integral curves and of filaments will be considered via a plug-in method using...
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作者：Su, Weijie; Candes, Emmanuel
作者单位：Stanford University; Stanford University
摘要：We consider high-dimensional sparse regression problems in which we observe y = X beta + z, where X is an n x p design matrix and z is an n dimensional vector of independent Gaussian errors, each with variance sigma(2). Our focus is on the recently introduced SLOPE estimator [Ann. Appi. Stat. 9 (2015) 1103-1140], which regularizes the least-squares estimates with the rank-dependent penalty Sigma(1 <= i <= p) lambda(i)vertical bar(beta) over cap vertical bar((i)), where vertical bar(beta) over ...
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作者：Gadat, Sebastien; Klein, Thierry; Marteau, Clement
作者单位：Universite de Toulouse; Universite Toulouse 1 Capitole; Toulouse School of Economics; Universite de Toulouse; Universite Toulouse III - Paul Sabatier; Centre National de la Recherche Scientifique (CNRS); Ecole Centrale de Lyon; Institut National des Sciences Appliquees de Lyon - INSA Lyon; Universite Claude Bernard Lyon 1; Universite Jean Monnet
摘要：Given an n-sample of random vectors (X-i, Y-i)(1 <= i <= n) whose joint law is unknown, the long-standing problem of supervised classification aims to optimally predict the label Y of a given new observation X. In this context, the k-nearest neighbor rule is a popular flexible and intuitive method in non parametric situations. Even if this algorithm is commonly used in the machine learning and statistics communities, less is known about its prediction ability in general finite dimensional spac...
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作者：Drees, Holger; Rootzen, Holger
作者单位：University of Hamburg; Chalmers University of Technology; University of Gothenburg
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作者：Bailey, R. A.; Brien, C. J.
作者单位：University of St Andrews; University of London; Queen Mary University London; University of South Australia; Australian Centre for Plant Functional Genomics; University of Adelaide
摘要：We derive randomization-based models for experiments with a chain of randomizations. Estimation theory for these models leads to formulae for the estimators of treatment effects, their standard errors and expected mean squares in the analysis of variance. We discuss the practicalities in fitting these models and outline the difficulties that can occur, many of which do not arise in two-tiered experiments.
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作者：Ke, Yuan; Li, Jialiang; Zhang, Wenyang
作者单位：Princeton University; National University of Singapore; University of York - UK
摘要：Panel data analysis is an important topic in statistics and econometrics. In such analysis, it is very common to assume the impact of a covariate on the response variable remains constant across all individuals. While the modelling based on this assumption is reasonable when only the global effect is of interest, in general, it may overlook some individual/subgroup attributes of the true covariate impact. In this paper, we propose a data driven approach to identify the groups in panel data wit...
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作者：Su, Yu-Ru; Wang, Jane-Ling
作者单位：Fred Hutchinson Cancer Center; University of California System; University of California Davis
摘要：In this paper, we investigate frailty models for clustered survival data that are subject to both left- and right-censoring, termed doubly-censored data. This model extends current survival literature by broadening the application of frailty models from right-censoring to a more complicated situation with additional left-censoring. Our approach is motivated by a recent Hepatitis B study where the sample consists of families. We adopt a likelihood approach that aims at the non parametric maximu...
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作者：Yoo, William Weimin; Ghosal, Subhashis
作者单位：Universite PSL; Universite Paris-Dauphine; North Carolina State University
摘要：In the setting of nonparametric multivariate regression with unknown error variance sigma(2), we study asymptotic properties of a Bayesian method for estimating a regression function f and its mixed partial derivatives. We use a random series of tensor product of B-splines with normal basis coefficients as a prior for f, and sigma is either estimated using the empirical Bayes approach or is endowed with a suitable prior in a hierarchical Bayes approach. We establish pointwise, L-2 and L-infini...
