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13 papers · 1 filter
Asymptotic equivalence and adaptive estimation for robust nonparametric regression
T. Tony Cai, Harrison H. Zhou
Asymptotic equivalence theory developed in the literature so far are only for bounded loss functions. This limits the potential applications of the theory because many commonly use…
Covariate-adjusted nonlinear regression
Xia Cui, Wensheng Guo, Lu Lin +1
In this paper, we propose a covariate-adjusted nonlinear regression model. In this model, both the response and predictors can only be observed after being distorted by some multip…
Nonparametric empirical Bayes and compound decision approaches to estimation of a high-dimensional vector of normal means
Lawrence D. Brown, Eitan Greenshtein
We consider the classical problem of estimating a vector $\boldsμ=(μ_1,...,μ_n)$ based on independent observations , . Suppose , are i…
Adaptive variance function estimation in heteroscedastic nonparametric regression
T. Tony Cai, Lie Wang
We consider a wavelet thresholding approach to adaptive variance function estimation in heteroscedastic nonparametric regression. A data-driven estimator is constructed by applying…
Functional principal components analysis via penalized rank one approximation
Jianhua Z. Huang, Haipeng Shen, Andreas Buja
Two existing approaches to functional principal components analysis (FPCA) are due to Rice and Silverman (1991) and Silverman (1996), both based on maximizing variance but introduc…
Admissible predictive density estimation
Lawrence D. Brown, Edward I. George, Xinyi Xu
Let and be independent -dimensional multivariate normal vectors with common unknown mean . Based on observing , we consider t…