hlm: Inference for a Heteroscedastic Linear Model

Martin Lysy, Tian You, Yifan Wang

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Description

Provides efficient algorithms to compute the MLE of a heteroscedastic regression model, with linear mean and log-linear variance covariates. An Expectation-Maximization algorithm is provided for right-censored responses, which are expected in the context of survival analysis for the corresponding heteroscedastic accelerated failure-time model of Wang et al (2019).

Installation

Install the R package devtools and run

devtools::install_github("mlysy/hlm")

Usage

The main function in the package is hlm(), which you would typically call like this:

M <- hlm(y ~ x1 + x2 | x1)

This would fit a heteroscedastic model with mean linear in x1 and x2, and variance log-linear in x1. For more examples please see ?hlm.