Results 11 to 20 of about 1,005 (119)
Selection of variables and dimension reduction in high-dimensional non-parametric regression [PDF]
, 2008 We consider a l1-penalization procedure in the non-parametric Gaussian regression model. In many concrete examples, the dimension d of the input variable X is very large (sometimes depending on the number of observations).
K. Bertin, G. Lecu'e
semanticscholar +1 more source
Instrumental variable regression via kernel maximum moment loss
Journal of Causal Inference, 2023 We investigate a simple objective for nonlinear instrumental variable (IV) regression based on a kernelized conditional moment restriction known as a maximum moment restriction (MMR).
Zhang Rui +3 more
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Localized deconvolution on the sphere [PDF]
, 2009 We provide a new algorithm for the treatment of deconvolutionon the sphere which combines the traditional SVD inversion withan appropriate thresholding technique in a well chosen new basis.We establish upper bounds for the behaviour of our procedure ...
G. Kerkyacharian +2 more
semanticscholar +1 more source
On the use of L-functionals in regression models
Open Mathematics, 2023 In this article, we survey and unify a large class or LL-functionals of the conditional distribution of the response variable in regression models.
Hössjer Ola, Karlsson Måns
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Majalah Ilmiah Matematika dan Statistika, 2022 Tuberculosis is a bacterial infection caused by Mycobacterium tuberculosis. Transmission of tuberculosis (TBC) can occur due to environmental factors and community behavior. West Java is Indonesia's province with the highest number of tuberculosis cases.
Niken Evitasari +2 more
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Significance testing in quantile regression [PDF]
, 2012 We consider the problem of testing significance of predictors in multivariate nonparametric quantile regression. A stochastic process is proposed, which is based on a comparison of the responses with a nonparametric quantile regression estimate under the
S. Volgushev +3 more
semanticscholar +1 more source
Complete consistency for the estimator of nonparametric regression model based on m-END errors
Open Mathematics, 2021 In this paper, we study the complete consistency for the estimator of nonparametric regression model based on m-END errors and obtain the convergence rates of the complete consistency under more general conditions.
Zhang Shui-Li, Hou Tiantian, Qu Cong
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Nonparametric relative recursive regression
Dependence Modeling, 2020 In this paper, we propose the problem of estimating a regression function recursively based on the minimization of the Mean Squared Relative Error (MSRE), where outlier data are present and the response variable of the model is positive.
Slaoui Yousri, Khardani Salah
doaj +1 more source
Oracally efficient estimation for single-index link function with simultaneous confidence band
, 2015 Over the last twenty-five years, various √ n-consistent estimators have been devised for the coefficient vector in the popular semiparametric single-index model.
Lijie Gu, Lijian Yang
semanticscholar +1 more source
PAC-Bayesian Aggregation of Affine Estimators [PDF]
, 2014 Aggregating estimators using exponential weights depending on their risk performs well in expectation, but sadly not in probability. Considering exponential weights of a penalized risk is a way to overcome this issue.
Lucie Montuelle, E. L. Pennec
semanticscholar +1 more source