High-dimensional generalized linear models

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WebRobust high-dimensional generalized linear models 33 functional T(F) is sufﬁciently regular, a von Mises expansion (von Mises, 1947) yields T(G) ... WebTony Cai, Zijian Guo, and Rong Ma. Abstract: This paper develops a unified statistical inference framework for high-dimensional binary generalized linear models (GLMs) with general link functions. Both unknown and known design distribution settings are considered. A two-step weighted bias-correction method is proposed for constructing ...

Graphical-model based high dimensional generalized linear models

WebA passionate and self-motivated data scientist with +5 years of experience in analytics domain, including wrangling, analyzing and modeling large … Web12 de fev. de 2024 · High-dimensional Generalized Linear Model (GLM) inferences have been studied by many scholars [3,4,5,6]. Deshpande proposed a debiasing method for constructing CIs. Cai, Athey and Zhu [8,9,10] proposed a more general linear comparison method under the condition of special load vectors. cigarette toxin crossword clue

Homogeneity detection for the high-dimensional generalized linear model ...

Web1 de jul. de 2024 · T-ridge estimator for generalized linear models. In this section, we exemplify the t-ridge estimator for maximum regularized likelihood estimation in generalized linear models. We consider data Z = ( y, X) that follow a conditional distribution (5) y i x i, β ∗ ∼ F with g ( E ( y i x i, β ∗)) = x i ⊤ β ∗. Webboth linear and logistic high-dimensional regression models. 2.1 Estimation in high-dimensional regression For the high-dimensional linear model (1), a commonly used … dhec drinking water branch

High-dimensional data and linear models: a review OAMS

High-dimensional generalized linear models

High-dimensional Inference for Generalized Linear Models with …

http://www-stat.wharton.upenn.edu/~tcai/paper/html/Inference-GLM.html http://www-stat.wharton.upenn.edu/~tcai/paper/html/Transfer-Learning-GLM.html

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Web25 de dez. de 2024 · Robust and consistent variable selection in high-dimensional generalized linear models - 24 Hours access EUR €36.00 GBP £32.00 USD $39.00 Rental. This article is also available for rental through DeepDyve. Advertisement. Citations. Views. 2,550. Altmetric. More metrics information. ×. Email alerts. Article activity alert. … WebAbstract. In this work, we study the transfer learning problem under high-dimensional generalized linear models (GLMs), which aim to improve the fit on target data by …

Webon high dimensional linear regression models, and it remains unknown whether their results can be extended to a more general setting. This paper will focus on … Web4 de abr. de 2008 · We consider high-dimensional generalized linear models with Lipschitz loss functions, and prove a nonasymptotic oracle inequality for the empirical …

Web7 de ago. de 2013 · This paper studies generalized additive partial linear models with high-dimensional covariates. We are interested in which components (including parametric and nonparametric components) are nonzero. The additive nonparametric functions are approximated by polynomial splines. WebAbstract. In this paper, we propose a sparse generalized linear model incorporating graphical structure among predictors (sGLMg), which is an extension of [37] where they exploit the structure information among predictors to improve the performance for the linear regression. There is an explicit expression between the coefficient and the ...

WebA Non-Asymptotic Moreau Envelope Theory for High-Dimensional Generalized Linear Models. Part of Advances in Neural Information Processing Systems 35 (NeurIPS 2024) Main Conference Track. Bibtex Paper Supplemental.

Web19 de fev. de 2014 · We consider testing regression coefficients in high dimensional generalized linear models. An investigation of the test of Goeman et al. (2011) is … cigarette tracker worksheetWebIn this paper, a graphic model-based doubly sparse regularized estimator is discussed under the high dimensional generalized linear models, that utilizes the graph … dhec drug inspectionWebHigh-dimensional Linear Discriminant Analysis: Optimality, Adaptive Algorithm, and Missing Data 1 T. Tony Cai and Linjun Zhang University of Pennsylvania Abstract This … cigarette toxins leachesWebIn this paper, a graphic model-based doubly sparse regularized estimator is discussed under the high dimensional generalized linear models, that utilizes the graph structure among the predictors. The graphic information among predictors is incorporated node-by-node using a decomposed representation and the sparsity is encouraged both within and ... dhec drive through covid testingWeb3 de fev. de 2024 · Variable selection in a grouped manner is an attractive method since it respects the grouping structure in the data. In this paper, we study the adaptive group Lasso in the frame of high-dimensional generalized linear models. Both the number of groups diverging with the sample size and the number of groups exceeding the sample … cigarette toxins effect bodyWeb16 de mar. de 2024 · This generalized form is an expansion and the resulting discriminant function is not linear in x, but it is linear in y. The d’-functions yi(x) merely map points in … dhec edge roadWebA Non-Asymptotic Moreau Envelope Theory for High-Dimensional Generalized Linear Models. Part of Advances in Neural Information Processing Systems 35 (NeurIPS 2024) … cigarette tubes for joints