High-dimensional generalized linear models
Webthe high-dimensional GLM transfer learning setting. Extensive simulations and a real-data experiment verify the e ectiveness of our algorithms. Keywords: Generalized linear … Web20 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 …
High-dimensional generalized linear models
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WebGeneralized linear model; High-dimensional inference; Matrix uncertainty selector; Measurement error; Sparse estimation; Acknowledgments. The authors would like to thank Prof. Bin Yu for discussions and Dr. Sjur Reppe for providing the bone density data. Reprints and Corporate Permissions. WebWe consider the lasso penalty for high-dimensional gener-alized linear models. Let Y ∈Y ⊂R be a real-valued (response) variable and X be a co-variable with values in some …
Web1 de jul. de 2024 · Many current intrinsically interpretable machine learning models can only handle the data that are linear, low-dimensional, and relatively independent attributes and often with discrete attribute values, while the models that are capable of handling high-dimensional nonlinear data, like deep learning, have very poor interpretability. WebVector autoregressive models characterize a variety of time series in which linear combinations of current and past observations can be used to accurately predict ...
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 ... WebIn 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 ...
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.
how many tenths in one inchWebTony Cai's Papers. Estimation and Inference for High-dimensional Generalized Linear Models with Knowledge Transfer. Sai Li, Linjun Zhang, Tony Cai, and Hongzhe Li. Abstract: Transfer learning provides a powerful tool for incorporating related data into a target study of interest. In epidemiology and medical studies, the classification of a ... how many tenths is 2.4http://www-stat.wharton.upenn.edu/~tcai/paper/html/Transfer-Learning-GLM.html how many tequila shots to get drunkhttp://www-stat.wharton.upenn.edu/~tcai/paper/html/Inference-GLM.html how many terabytes are in a zettabyteWeb3 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 … how many tenths of an hourWeb10 de abr. de 2024 · In both cases, models that are based on pairwise covariances can be used on their own or as an element in a larger model, such as a spatial generalized linear model. In this work, we are mainly concerned with using spatial information to improve the accuracy of predictions, rather than reducing bias in parameter estimates ( LeSage, 2008 ). how many terabytes are in a gigabyteWebIn 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 borrowing information from useful source data. Given which sources to transfer, we propose a transfer learning algorithm on GLM, ... how many terabytes can fit on an hdd