Image de couverture de livre

A constrained iteratively-reweighted least-squares framework for generalised linear models

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Masselot, Pierre, Nenon, Devon, Vanoli, Jacopo, Chalabi, Zaid, Gasparrini, Antonio
Format:	Preprint
Publié:	2025
Sujets:	Methodology
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

Scalable approximation of the transformation-free linear simplicial-simplicial regression via constrained iterative reweighted least squares
par: Tsagris, Michail, et autres
Publié: (2025)

Weighted least squares estimation by multivariate-dependent weights for linear regression models
par: Huang, Lei, et autres
Publié: (2026)

Spatially varying distributed lag non-linear models using Laplacian P-splines
par: Rutten, Sara, et autres
Publié: (2026)

Distributed lag non-linear models with spatial effect modification using Laplacian P-splines
par: Rutten, Sara, et autres
Publié: (2026)

A penalized least squares estimator for extreme-value mixture models
par: Mourahib, Anas, et autres
Publié: (2025)

Constrained least squares simplicial-simplicial regression
par: Tsagris, Michail
Publié: (2024)

Subscedastic weighted least squares estimates
par: Bryan, Jordan, et autres
Publié: (2024)

Envelope-based partial least squares in functional regression
par: Wu, Minxuan, et autres
Publié: (2025)

Sensitivity of weighted least squares estimators to omitted variables
par: Wainstein, Leonard, et autres
Publié: (2025)

Profile least squares estimation in networks with covariates
par: Chandna, Swati, et autres
Publié: (2024)

Simulation study to evaluate when Plasmode simulation is superior to parametric simulation in estimating the mean squared error of the least squares estimator in linear regression
par: Stolte, Marieke, et autres
Publié: (2023)

Ridge-penalised spectral least-squares estimation for point processes
par: Herrera, Miguel Martinez, et autres
Publié: (2026)

Multivariate moment least-squares estimators for reversible Markov chains
par: Song, Hyebin, et autres
Publié: (2023)

Phylogenetic least squares estimation without genetic distances
par: Chi, Peter B., et autres
Publié: (2023)

Uncertainty quantification for iterative algorithms in linear models with application to early stopping
par: Bellec, Pierre C., et autres
Publié: (2024)

Predicting milk traits from spectral data using Bayesian probabilistic partial least squares regression
par: Urbas, Szymon, et autres
Publié: (2023)

Two-stage least squares with treatment-covariate interactions for treatment effect heterogeneity
par: Zhao, Anqi, et autres
Publié: (2025)

Two-stage weighted least squares estimator of multivariate non-negative observation-driven models
par: Armillotta, Mirko
Publié: (2023)

Precise asymptotics of reweighted least-squares algorithms for linear diagonal networks
par: Kaushik, Chiraag, et autres
Publié: (2024)

Identification enhanced generalised linear model estimation with nonignorable missing outcomes
par: Beppu, Kenji, et autres
Publié: (2022)

Structured Lasso for convex nonparametric least squares: An application to Swedish electricity distribution networks
par: Liao, Zhiqiang, et autres
Publié: (2024)

Recent advances in doubly-robust weighted ordinary least squares techniques for dynamic treatment regime estimation
par: Nadi, Adel Ahmadi, et autres
Publié: (2025)

Statistical inference for partially shape-constrained function-on-scalar linear regression models
par: Han, Kyunghee, et autres
Publié: (2024)

A general formulation of reweighted least squares fitting
par: Giannelli, Carlotta, et autres
Publié: (2024)

Semi-parametric least-area linear-circular regression through Möbius transformation
par: Biswas, Surojit, et autres
Publié: (2024)

Generalised least squares approach for estimation of the log-law parameters of turbulent boundary layers
par: Ferreira, M. Aguiar, et autres
Publié: (2026)

With random regressors, least squares inference is robust to correlated errors with unknown correlation structure
par: Zhang, Zifeng, et autres
Publié: (2024)

Fast algorithm for sparse least trimmed squares via trimmed-regularized reformulation
par: Yagishita, Shotaro
Publié: (2024)

Ridge, lasso, and elastic-net estimations of the modified Poisson and least-squares regressions for binary outcome data
par: Kitano, Takahiro, et autres
Publié: (2024)

Sparse higher order partial least squares for simultaneous variable selection, dimension reduction, and tensor denoising
par: Park, Kwangmoon, et autres
Publié: (2023)

Bayesian iterative screening in ultra-high dimensional linear regressions
par: Wang, Run, et autres
Publié: (2021)

Identifiability and improper solutions in the probabilistic partial least squares regression with unique variance
par: Arai, Takashi
Publié: (2025)

A joint optimization approach to identifying sparse dynamics using least squares kernel collocation
par: Hsu, Alexander W., et autres
Publié: (2025)

Orthogonal Arrays: A Review
par: Lin, C. Devon, et autres
Publié: (2025)

Scoping review of methodology for aiding generalisability and transportability of clinical prediction models
par: Ploddi, Kritchavat, et autres
Publié: (2024)

Flexible extreme thresholds through generalised Bayesian model averaging
par: Jessup, Sébastien, et autres
Publié: (2025)

A generalised discrete mixture model to better capture preference heterogeneity in discrete choice data
par: Hancock, Thomas O., et autres
Publié: (2025)

Coherent forecast combination for linearly constrained multiple time series
par: Girolimetto, Daniele, et autres
Publié: (2024)

Unbiased least squares regression via averaged stochastic gradient descent
par: Kahalé, Nabil
Publié: (2024)

Statistical inference for large-dimensional tensor factor model by iterative projections
par: Barigozzi, Matteo, et autres
Publié: (2022)