Work

VarReg: An R package for semi-parametric variance regression

Year: 2026

Type: software-paper

Abstract: Variance regression is used to model heteroscedasticity in terms of covariates. Algorithms already exist but they may face computational instability due to the required parameter constraints. Therefore, having a suite of tools based on a variety of computational methods is essential. Here we present VarReg, an R package that fits variance regression models using a stable expectation-maximisation approach, which can incorporate flexible splines. VarReg accommodates censored and skewed data and allows regression models for shape parameters as well as location and scale. VarReg’s functions are demonstrated with real-world examples, illustrating a valuable, stable package for fitting these complex regression models.

Source: SoftwareX

DOI: 10.1016/j.softx.2026.102553

Authors: Kristy P Robledo, Ian C Marschner

Institutions: The University of Sydney, National Health and Medical Research Council

Language: English

Topic: Statistical Distribution Estimation and Applications

Subfield: Statistics and Probability

Field: Mathematics

Domain: Physical Sciences

Open Access status: gold

Estimated APC paid: $1,200

Funder: National Health and Medical Research Council