Imagen de Portada

Scalable approximation of the transformation-free linear simplicial-simplicial regression via constrained iterative reweighted least squares

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autores principales:	Tsagris, Michail, Alzeley, Omar
Formato:	Preprint
Publicado:	2025
Materias:	Methodology Computation
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

Constrained least squares simplicial-simplicial regression
por: Tsagris, Michail
Publicado: (2024)

Circular and Spherical Projected Cauchy Distributions: A Novel Framework for Circular and Directional Data Modeling
por: Tsagris, Michail, et al.
Publicado: (2023)

A constrained iteratively-reweighted least-squares framework for generalised linear models
por: Masselot, Pierre, et al.
Publicado: (2025)

The $α$--regression for compositional data: a unified framework for standard, temporal and spatial regression models including compositional predictors
por: Tsagris, Michail, et al.
Publicado: (2025)

On the generalized circular projected Cauchy distribution
por: Alzeley, Omar, et al.
Publicado: (2026)

Simplicial clustering using the $α$--transformation
por: Tsagris, Michail, et al.
Publicado: (2025)

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
por: Stolte, Marieke, et al.
Publicado: (2023)

Enhanced Lepage-type test statistics for location-scale shifts with right-skewed data
por: Hussain, Abid, et al.
Publicado: (2025)

Energy Based Equality of Distributions Testing for Compositional Data
por: Sevinc, Volkan, et al.
Publicado: (2024)

Weighted least squares estimation by multivariate-dependent weights for linear regression models
por: Huang, Lei, et al.
Publicado: (2026)

Semi-parametric least-area linear-circular regression through Möbius transformation
por: Biswas, Surojit, et al.
Publicado: (2024)

Envelope-based partial least squares in functional regression
por: Wu, Minxuan, et al.
Publicado: (2025)

On independence testing using the (partial) distance correlation
por: Nikolaos, Kontemeniotis, et al.
Publicado: (2025)

Model--based clustering for spherical and hyper--spherical data using elliptically symmetric distributions
por: Perdikis, Theodoros, et al.
Publicado: (2026)

Directional data analysis using the spherical Cauchy and the Poisson kernel-based distribution
por: Tsagris, Michail, et al.
Publicado: (2024)

A Jensen-Shannon divergence based $k$--$NN$ algorithm for missing value imputation in compositional data
por: Tsagris, Michail, et al.
Publicado: (2026)

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

Bayesian iterative screening in ultra-high dimensional linear regressions
por: Wang, Run, et al.
Publicado: (2021)

Least trimmed squares regression with missing values and cellwise outliers
por: Raymaekers, Jakob, et al.
Publicado: (2026)

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

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

Ridge, lasso, and elastic-net estimations of the modified Poisson and least-squares regressions for binary outcome data
por: Kitano, Takahiro, et al.
Publicado: (2024)

Predicting milk traits from spectral data using Bayesian probabilistic partial least squares regression
por: Urbas, Szymon, et al.
Publicado: (2023)

Interval-censored linear quantile regression
por: Choi, Taehwa, et al.
Publicado: (2024)

Circular and spherical projected Cauchy distributions: A novel framework for directional data modelling
por: M. Tsagris, et al.
Publicado: (2025)

Statistical inference for partially shape-constrained function-on-scalar linear regression models
por: Han, Kyunghee, et al.
Publicado: (2024)

Variational approximate penalized credible regions for Bayesian grouped regression
por: Yu, Weichang, et al.
Publicado: (2026)

Subscedastic weighted least squares estimates
por: Bryan, Jordan, et al.
Publicado: (2024)

Sensitivity of weighted least squares estimators to omitted variables
por: Wainstein, Leonard, et al.
Publicado: (2025)

Profile least squares estimation in networks with covariates
por: Chandna, Swati, et al.
Publicado: (2024)

Scalable Bayesian inference on high-dimensional multivariate linear regression
por: Cao, Xuan, et al.
Publicado: (2025)

Ridge-penalised spectral least-squares estimation for point processes
por: Herrera, Miguel Martinez, et al.
Publicado: (2026)

Multivariate moment least-squares estimators for reversible Markov chains
por: Song, Hyebin, et al.
Publicado: (2023)

Renewable estimation in linear expectile regression models with streaming data sets
por: Cao, Wei, et al.
Publicado: (2026)

Coherent forecast combination for linearly constrained multiple time series
por: Girolimetto, Daniele, et al.
Publicado: (2024)

On synthetic interval data with predetermined subject partitioning, and partial control of the variables' marginal correlation structure
por: Papathomas, Michail
Publicado: (2017)

Numerically robust square root implementations of statistical linear regression filters and smoothers
por: Tronarp, Filip
Publicado: (2024)

The Generalized Elastic Net for least squares regression with network-aligned signal and correlated design
por: Tran, Huy, et al.
Publicado: (2022)

A penalized least squares estimator for extreme-value mixture models
por: Mourahib, Anas, et al.
Publicado: (2025)

Phylogenetic least squares estimation without genetic distances
por: Chi, Peter B., et al.
Publicado: (2023)