High-dimensional partially linear model

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August undefined, 2024

Web7 de nov. de 2024 · This paper considers tests for regression coefficients in high dimensional partially linear Models. The authors first use the B-spline method to estimate the unknown smooth function so that it could be linearly expressed. Then, the authors propose an empirical likelihood method to test regression coefficients. The authors … WebPartially linear models attract much attention to investigate the association between predictors and the response variable when the dependency on some predictors may be …

SCAD-penalized regression in high-dimensional partially linear models

WebAbstract. We consider the problem of simultaneous variable selection and estimation in partially linear models with a divergent number of covariates in the linear part, under the assumption that the vector of regression coefficients is sparse. We apply the SCAD penalty to achieve sparsity in the linear part and use polynomial splines to ... Web18 de out. de 2024 · Download PDF Abstract: This paper considers the partially functional linear model (PFLM) where all predictive features consist of a functional covariate and a high dimensional scalar vector. Over an infinite dimensional reproducing kernel Hilbert space, the proposed estimation for PFLM is a least square approach with two mixed … cryptopsy - slit your guts

Variable selection for partially linear models via partial correlation

Web31 de mar. de 2009 · SCAD-penalized regression in high-dimensional partially linear models. We consider the problem of simultaneous variable selection and estimation in … Web7 de ago. de 2013 · An RKHS-based approach to double-penalized regression in high-dimensional partially linear models. Journal of Multivariate Analysis, Vol. 168, Issue. , p. 201. CrossRef; Google Scholar; Zhang, Jun and Lian, Heng 2024. Partially Linear Additive Models with Unknown Link Functions. Web29 de mar. de 2024 · We consider a semiparametric additive partially linear regression model (APLM) for analysing ultra-high-dimensional data where both the number of … dutch canopy for homes

Ultra high-dimensional semiparametric longitudinal data analysis

Web18 de ago. de 2024 · To address these issues, the current paper proposes a new communication-efficient distributed learning algorithm for partially sparse linear models … WebWe consider a flexible semiparametric approach, namely, partially linear single-index models, for ultra high-dimensional longitudinal data. Most importantly, we allow not … dutch canopy awningsWebHigh-dimensional PLM AMS 2000 subject classiﬁcation. Primary 62J05, 62G08; secondary 62E20 1. Introduction. Consider a partially linear model (PLM) Y = X0ﬂ +g(T)+"; where ﬂ is a p £ 1 vector of regression coefﬁcients associated with X, and g is an unknown function of T. In this model, the mean response is linearly related to X, while ... dutch car pack lspdfr

"Web1 de out. de 2024 · Guo et al. (2024) study a statistical inference procedure in the high-dimensional linear mediation models. They propose a new F-type test for the direct and indirect effects and also develop its theoretical properties. Luo et al. (2024) extend the methodologies to a survival outcome for settings with high-dimensional mediators. " - High-dimensional partially linear model

High-dimensional partially linear model

For high-dimensional hierarchical models, consider …

WebPerson as author : Pontier, L. In : Methodology of plant eco-physiology: proceedings of the Montpellier Symposium, p. 77-82, illus. Language : French Year of publication : 1965. book part. METHODOLOGY OF PLANT ECO-PHYSIOLOGY Proceedings of the Montpellier Symposium Edited by F. E. ECKARDT MÉTHODOLOGIE DE L'ÉCO- PHYSIOLOGIE … Websult empirically on several high-dimensional multiple regression and classiﬁcation problems. 1 Introduction Hierarchical modeling is a mainstay of Bayesian inference. For instance, in (generalized) linear models, the unknown parameters are effects, each of which describes the association of a particular covariate with a response of interest.

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Web24 de mai. de 2024 · Download PDF Abstract: This paper proposes a regularized pairwise difference approach for estimating the linear component coefficient in a partially linear model, with consistency and exact rates of convergence obtained in high dimensions under mild scaling requirements. Our analysis reveals interesting features such as (i) the … http://proceedings.mlr.press/v89/zhu19c/zhu19c.pdf

WebIn this paper, we study ultra-high-dimensional partially linear models when the dimension of the linear predictors grows exponentially with the sample size. For the variable screening, we propose a sequential profile Lasso method (SPLasso) and show that it possesses the screening property. Web1 de set. de 2013 · In this example, we consider the proposed variable selection procedure (BAS-ACQR) for n = 200, d = 400 in (3.1) (i.e., the number of nonzero coefficients in the linear part is 3 and that of zero coefficients is 397). The results of variable selection are reported in Table 1.Here, ACQR1 and ACQR2 represent the proposed BAS-ACQR …

Web1 de set. de 2013 · We generate data from the following additive partial linear model Y i = ∑ l = 1 d X i l α l + ∑ j = 1 p g j (Z i j) + ε i, i = 1, …, n with n being the sample size, d being … WebThe partially linear model (PLM) is a useful semiparametric extension of the linear model that has been well studied in the statistical literature. ... Grouped variable selection in …

Webtion in partially linear models with a divergent number of covariates in the linear part, under the assumption that the vector of regression coefficients is sparse. We apply the …

Web8 de ago. de 2024 · proposed the debiased Lasso for high dimensional linear models. These estimators are non-sparse, have a limiting normal distribution, and do not require … dutch canyon oregonWeb摘要： This paper analyzes a new regularized learning scheme for high-dimensional partially linear support vector machine (SVM). The proposed approach consists of an … cryptops hortensisWebWe consider a flexible semiparametric approach, namely, partially linear single-index models, for ultra high-dimensional longitudinal data. Most importantly, we allow not only the partially linear covariates but also the single-index covariates within the unknown flexible function estimated nonparametrically to be ultra high dimensional. dutch capuchine rock pigeonWeb3 de jul. de 2013 · It is shown that a high‐dimensional linear part can be estimated with oracle rates, using the least absolute shrinkage and selection operator penalty for the linear part and a smoothness Penalty for the nonparametric part. Partial linear models have been widely used as flexible method for modelling linear components in conjunction with … dutch carbon consultancyWeb29 de mar. de 2024 · We consider a semiparametric additive partially linear regression model (APLM) for analysing ultra-high-dimensional data where both the number of … dutch canyon drinkWebAND PARAMETRIC PARTS IN HIGH-DIMENSIONAL PARTIALLY LINEAR ADDITIVE MODELS Heng Lian, Hua Liang and David Ruppert University of New South Wales, George Washington University ... a result, the partially linear additive model, a more parsimonious special case of (1.1), has been proposed and studied (Opsomer and Ruppert (1999); Liu, … cryptopsy alex auburnWeb10 de set. de 2024 · Distributed Partially Linear Additive Models With a High Dimensional Linear Part Abstract: We study how the divide and conquer principle works in high-dimensional partially linear additive models when the dimension of the linear part is … cryptopsy blasphemy made flesh rar