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作者：Tibshirani, Ryan J.; Taylor, Jonathan; Lockhart, Richard; Tibshirani, Robert
作者单位：Carnegie Mellon University; Carnegie Mellon University
摘要：We propose new inference tools for forward stepwise regression, least angle regression, and the lasso. Assuming a Gaussian model for the observation vector y, we first describe a general scheme to perform valid inference after any selection event that can be characterized as y falling into a polyhedral set. This framework allows us to derive conditional (post-selection) hypothesis tests at any step of forward stepwise or least angle regression, or any step along the lasso regularization path, ...
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作者：Feng, Xingdong; Zhu, Liping
作者单位：Shanghai University of Finance & Economics; Renmin University of China
摘要：In this article, we establish a novel connection between the null hypothesis H-0 on the coefficients and a rank-reducible form of the varying coefficient model in quantile regression. We use B-splines to approximate the varying coefficients in the rank-reducible model, and make use of the fact that the null hypothesis H-0 implies a unidimensional structure of a transformed coefficient matrix for the B-spline basis functions. By evaluating the unidimensional structure, we alleviate the difficul...
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作者：Bagchi, Pramita; Banerjee, Moulinath; Stoev, Stilian A.
作者单位：Ruhr University Bochum; University of Michigan System; University of Michigan
摘要：We introduce new point-wise confidence interval estimates for monotone functions observed with additive, dependent noise. Our methodology applies to both short- and long-range dependence regimes for the errors. The interval estimates are obtained via the method of inversion of certain discrepancy statistics. This approach avoids the estimation of nuisance parameters such as the derivative of the unknown function, which previous methods are forced to deal with. The resulting estimates are there...
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作者：Fiecas, Mark; Ombao, Hernando
作者单位：University of Warwick; University of California System; University of California Irvine
摘要：We develop a new time series model to investigate the dynamic interactions between the nucleus accumbens and the hippocampus during an associative learning experiment. Preliminary analyses indicated that the spectral properties of the local field potentials at these two regions changed over the trials of the experiment. While many models already take into account nonstationarity within a single trial, the evolution of the dynamics across trials is often ignored. Our proposed model, the slowly ...
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作者：Qian, Min
作者单位：Columbia University
摘要：This comment deals with issues related to the article by Chen, Zeng, and Kosorok. We present several potential modifications of the outcome weighted learning approach.Those modifications are basecIon truncated l(2) loss. One advantage of l(2) loss is that it is differentiable everywhere, which makes it more stable and computationally more tractable.
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作者：Bennett, Christopher J.; Thompson, Brennan S.
作者单位：Toronto Metropolitan University
摘要：It has been more than half a century since Tukey first introduced graphical displays that relate nonoverlap of confidence intervals to statistically significant differences between parameter estimates. In this article, we show how Tukey's graphical overlap procedure can be modified to accommodate general forms of dependence within and across samples. We also develop a procedure that can be used to more effectively resolve rankings within the tails of the distributions of parameter values, ther...
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作者：Guo, Jianhua; Hu, Jianchang; Jing, Bing-Yi; Zhang, Zhen
作者单位：Hong Kong University of Science & Technology; National University of Singapore
摘要：We consider a high-dimensional linear regression problem, where the covariates (features) are ordered in some meaningful way, and the number of covariates p can be much larger than the sample size n. The fused lasso of Tibshirani et al. is designed especially to tackle this type of problems; it yields sparse coefficients and selects grouped variables, and encourages local constant coefficient profile within each group. However, in some applications, the effects of different features within a g...
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作者：Ogburn, Elizabeth L.
作者单位：Johns Hopkins University
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作者：Huang, Chiung-Yu; Qin, Jing; Tsai, Huei-Ting
作者单位：Johns Hopkins University; Johns Hopkins Medicine
摘要：With the rapidly increasing availability of data in the public domain, combining information from different sources to infer about associations or differences of interest has become an emerging challenge to researchers. This article presents a novel approach to improve efficiency in estimating the survival time distribution by synthesizing information from the individual-level data with t-year survival probabilities from external sources such as disease registries. While disease registries pro...
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作者：Liang, Faming; Jin, Ick Hoon; Song, Qifan; Liu, Jun S.
作者单位：State University System of Florida; University of Florida; University of Notre Dame; University System of Ohio; Ohio State University; Purdue University System; Purdue University; Harvard University
摘要：Sampling from the posterior distribution for a model whose normalizing constant is intractable is a long-standing problem in statistical research. We propose a new algorithm, adaptive auxiliary variable exchange algorithm, or, in short, adaptive exchange (AEX) algorithm, to tackle this problem. The new algorithm can be viewed as a MCMC extension of the exchange algorithm, which generates auxiliary variables via an importance sampling procedure from a Markov chain running in parallel. The conve...
