Journal of the Royal Statistical Society: Series B

最新文章

• Non-parametric tests for distributional treatment effect for randomly censored responses AI翻译
  作者：Lee, Myoung-jae
  作者单位：Korea University
  摘要：For a binary treatment nu=0, 1 and the corresponding 'potential response'Y-0 for the control group (nu=0) and Y-1 for the treatment group (nu=1), one definition of no treatment effect is that Y-0 and Y-1 follow the same distribution given a covariate vector X. Koul and Schick have provided a non-parametric test for no distributional effect when the realized response (1-nu)Y-0+nu Y-1 is fully observed and the distribution of X is the same across the two groups. This test is thus not applicable ...
• Shrinkage inverse regression estimation for model-free variable selection AI翻译
  作者：Bondell, Howard D.; Li, Lexin
  作者单位：North Carolina State University
  摘要：The family of inverse regression estimators that was recently proposed by Cook and Ni has proven effective in dimension reduction by transforming the high dimensional predictor vector to its low dimensional projections. We propose a general shrinkage estimation strategy for the entire inverse regression estimation family that is capable of simultaneous dimension reduction and variable selection. We demonstrate that the new estimators achieve consistency in variable selection without requiring ...
• Bayesian model selection using test statistics AI翻译
  作者：Hu, Jianhua; Johnson, Valen E.
  作者单位：University of Texas System; UTMD Anderson Cancer Center
  摘要：Existing Bayesian model selection procedures require the specification of prior distributions on the parameters appearing in every model in the selection set. In practice, this requirement limits the application of Bayesian model selection methodology. To overcome this limitation, we propose a new approach towards Bayesian model selection that uses classical test statistics to compute Bayes factors between possible models. In several test cases, our approach produces results that are similar t...
• Adaptively varying-coefficient spatiotemporal models AI翻译
  作者：Lu, Zudi; Steinskog, Dag Johan; Tjostheim, Dag; Yao, Qiwei
  作者单位：University of Bergen; University of London; London School Economics & Political Science; Curtin University; University of Adelaide; Nansen Environmental & Remote Sensing Center (NERSC); Bjerknes Centre for Climate Research; Peking University
  摘要：We propose an adaptive varying-coefficient spatiotemporal model for data that are observed irregularly over space and regularly in time. The model is capable of catching possible non-linearity (both in space and in time) and non-stationarity (in space) by allowing the auto-regressive coefficients to vary with both spatial location and an unknown index variable. We suggest a two-step procedure to estimate both the coefficient functions and the index variable, which is readily implemented and ca...
• Testing for lack of fit in inverse regression-with applications to biophotonic imaging AI翻译
  作者：Bissantz, Nicolai; Claeskens, Gerda; Holzmann, Hajo; Munk, Axel
  作者单位：Ruhr University Bochum; KU Leuven; Helmholtz Association; Karlsruhe Institute of Technology; University of Gottingen
  摘要：We propose two test statistics for use in inverse regression problems Y=K theta+epsilon, where K is a given linear operator which cannot be continuously inverted. Thus, only noisy, indirect observations Y for the function theta are available. Both test statistics have a counterpart in classical hypothesis testing, where they are called the order selection test and the data-driven Neyman smooth test. We also introduce two model selection criteria which extend the classical Akaike information cr...
• Covariance-regularized regression and classification for high dimensional problems AI翻译
  作者：Witten, Daniela M.; Tibshirani, Robert
  作者单位：Stanford University
  摘要：We propose covariance-regularized regression, a family of methods for prediction in high dimensional settings that uses a shrunken estimate of the inverse covariance matrix of the features to achieve superior prediction. An estimate of the inverse covariance matrix is obtained by maximizing the log-likelihood of the data, under a multivariate normal model, subject to a penalty; it is then used to estimate coefficients for the regression of the response onto the features. We show that ridge reg...
• Copula structure analysis AI翻译
  作者：Klueppelberg, Claudia; Kuhn, Gabriel
  作者单位：Technical University of Munich
  摘要：We extend the standard approach of correlation structure analysis for dimension reduction of high dimensional statistical data. The classical assumption of a linear model for the distribution of a random vector is replaced by the weaker assumption of a model for the copula. For elliptical copulas a correlation-like structure remains, but different margins and non-existence of moments are possible. After introducing the new concept and deriving some theoretical results we observe in a simulatio...
• Testing in semiparametric models with interaction, with applications to gene-environment interactions AI翻译
  作者：Maity, Arnab; Carroll, Raymond J.; Mammen, Enno; Chatterjee, Nilanjan
  作者单位：Texas A&M University System; Texas A&M University College Station; University of Mannheim; National Institutes of Health (NIH) - USA; NIH National Cancer Institute (NCI)
  摘要：Motivated from the problem of testing for genetic effects on complex traits in the presence of gene-environment interaction, we develop score tests in general semiparametric regression problems that involves Tukey style 1 degree-of-freedom form of interaction between parametrically and non-parametrically modelled covariates. We find that the score test in this type of model, as recently developed by Chatterjee and co-workers in the fully parametric setting, is biased and requires undersmoothin...
• Parameter estimation for partially observed hypoelliptic diffusions AI翻译
  作者：Pokern, Yvo; Stuart, Andrew M.; Wiberg, Petter
  作者单位：University of Warwick
  摘要：Hypoelliptic diffusion processes can be used to model a variety of phenomena in applications ranging from molecular dynamics to audio signal analysis. We study parameter estimation for such processes in situations where we observe some components of the solution at discrete times. Since exact likelihoods for the transition densities are typically not known, approximations are used that are expected to work well in the limit of small intersample times Delta t and large total observation times N...
• A Bayesian approach to non-parametric monotone function estimation AI翻译
  作者：Shively, Thomas S.; Sager, Thomas W.; Walker, Stephen G.
  作者单位：University of Texas System; University of Texas Austin; University of Kent
  摘要：The paper proposes two Bayesian approaches to non-parametric monotone function estimation. The first approach uses a hierarchical Bayes framework and a characterization of smooth monotone functions given by Ramsay that allows unconstrained estimation. The second approach uses a Bayesian regression spline model of Smith and Kohn with a mixture distribution of constrained normal distributions as the prior for the regression coefficients to ensure the monotonicity of the resulting function estima...