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Bibliographic Details
Main Authors:	Tsagris, Michail, Alzeley, Omar
Format:	Preprint
Published:	2025
Subjects:	Methodology Computation
Online Access:	https://arxiv.org/abs/2511.13296
Tags:	Add Tag No Tags, Be the first to tag this record!

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

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

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

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

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

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

Energy Based Equality of Distributions Testing for Compositional Data
by: Sevinc, Volkan, et al.
Published: (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
by: Stolte, Marieke, et al.
Published: (2023)

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Subscedastic weighted least squares estimates
by: Bryan, Jordan, et al.
Published: (2024)

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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