Results 1 to 10 of about 1,274,599 (258)
Elastic Net Regularization Paths for All Generalized Linear Models [PDF]
Journal of Statistical Software, 2023 The lasso and elastic net are popular regularized regression models for supervised learning. Friedman, Hastie, and Tibshirani (2010) introduced a computationally efficient algorithm for computing the elastic net regularization path for ordinary least ...
J. Kenneth Tay +2 more
doaj +2 more sources
Feature Screening for High-Dimensional Variable Selection in Generalized Linear Models [PDF]
Entropy, 2023 The two-stage feature screening method for linear models applies dimension reduction at first stage to screen out nuisance features and dramatically reduce the dimension to a moderate size; at the second stage, penalized methods such as LASSO and SCAD ...
Jinzhu Jiang, Junfeng Shang
doaj +2 more sources
Hierarchical Generalized Linear Models: The R Package HGLMMM [PDF]
Journal of Statistical Software, 2011 The R package HGLMMM has been developed to fit generalized linear models with random effects using the h-likelihood approach. The response variable is allowed to follow a binomial, Poisson, Gaussian or gamma distribution.
Marek Molas, Emmanuel Lesaffre
doaj +1 more source
Generalized Linear Models with Covariate Measurement Error and Zero-Inflated Surrogates [PDF]
MathematicsEpidemiological studies often encounter a challenge due to exposure measurement error when estimating an exposure–disease association. A surrogate variable may be available for the true unobserved exposure variable.
Ching-Yun Wang +3 more
doaj +2 more sources
Regularization Paths for Generalized Linear Models via Coordinate Descent [PDF]
Journal of Statistical Software, 2010 We develop fast algorithms for estimation of generalized linear models with convex penalties. The models include linear regression, two-class logistic regression, and multi- nomial regression problems while the penalties include ℓ1 (the lasso), ℓ2 (ridge
Jerome Friedman +2 more
doaj +1 more source
partR2: partitioning R2 in generalized linear mixed models [PDF]
PeerJ, 2021 The coefficient of determination R2 quantifies the amount of variance explained by regression coefficients in a linear model. It can be seen as the fixed-effects complement to the repeatability R (intra-class correlation) for the variance explained by ...
Martin A. Stoffel +2 more
doaj +2 more sources
CytoGLMM: conditional differential analysis for flow and mass cytometry experiments
BMC Bioinformatics, 2021 Background Flow and mass cytometry are important modern immunology tools for measuring expression levels of multiple proteins on single cells. The goal is to better understand the mechanisms of responses on a single cell basis by studying differential ...
Christof Seiler +7 more
doaj +1 more source
Bias-Corrected Inference of High-Dimensional Generalized Linear Models
Mathematics, 2023 In this paper, we propose a weighted link-specific (WLS) approach that establishes a unified statistical inference framework for high-dimensional Poisson and Gamma regression.
Shengfei Tang, Yanmei Shi, Qi Zhang
doaj +1 more source
Semina: Ciências Exatas e Tecnológicas, 2021 Generalized additive models for location, scale and shape (GAMLSS) are a very flexible statistical modeling framework, being an important generalization of the well-known generalized linear models and generalized additive models.
Fernanda V. Roquim +5 more
doaj +1 more source
Nonparametric inference in generalized functional linear models [PDF]
, 2015 We propose a roughness regularization approach in making nonparametric inference for generalized functional linear models. In a reproducing kernel Hilbert space framework, we construct asymptotically valid confidence intervals for regression mean ...
Cheng, Guang, Shang, Zuofeng
core +1 more source