A general algorithm for error-in-variables regression modelling using Monte Carlo expectation maximization.

A general algorithm for error-in-variables regression modelling using Monte Carlo expectation maximization.

In regression modelling, measurement error models are often needed to correct for uncertainty arising from measurements of covariates/predictor variables. The literature on measurement error (or errors-in-variables) modelling is plentiful, however, general algorithms and software for maximum likelih...

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Bibliographic Details
Main Authors: Jakub Stoklosa, Wen-Han Hwang, David I Warton
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2023-01-01
Series:PLoS ONE
Online Access:https://doi.org/10.1371/journal.pone.0283798

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