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2024 | OriginalPaper | Chapter

Fitting Regression Models When Both Variables Are Subject to Non-normal Error Terms

Authors : Abed Al-Hakim Majdalawi, Amjad D. Al-Nasser

Published in: Mathematical Analysis and Numerical Methods

Publisher: Springer Nature Singapore

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Abstract

This paper explores the structural measurement error model under the assumption of non-normal distribution for the error terms, specifically following the Exponential distribution. The article considers the use of non-identical distributions for the error terms and employs the Method of Moments (MOM) to estimate the unknown parameters based on these pre-assumptions. Real data on the relationships between Man-Hours and Workload are utilized to evaluate the performance of the estimators. Additionally, the precision of the estimators is compared with Wald-type grouping estimators. The findings of the analysis reveal that the grouping methods outperform the MOM in terms of fitting the non-normal structural measurement error model, as evidenced by lower mean squared error (MSE).

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previous chapter Large Family of Quaternary Sequences with High Linear Complexity and Period
next chapter Structure of Cyclotomic Polynomials and Several Applications
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Metadata
Title
Fitting Regression Models When Both Variables Are Subject to Non-normal Error Terms
Authors
Abed Al-Hakim Majdalawi
Amjad D. Al-Nasser
Copyright Year
2024
Publisher
Springer Nature Singapore
Book
Mathematical Analysis and Numerical Methods

Print ISBN: 978-981-9748-75-4

Electronic ISBN: 978-981-9748-76-1

Copyright Year: 2024

DOI
https://doi.org/10.1007/978-981-97-4876-1_13

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