TY - GEN
T1 - Multiple Linear Regression Applications and Multicollinearity
T2 - 8th World Conference on Smart Trends in Systems Security and Sustainability, WorldS4 2024
AU - Morejon, Maricela Fernanda Ormaza
AU - Moreira, Rolando Ismael Yépez
AU - Buenaño, Edison Noe Buenaño
AU - Allaica, Juan Carlos Muyulema
N1 - Publisher Copyright:
© The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.
PY - 2025
Y1 - 2025
N2 - The bibliometric study addresses the scientific production employing multiple linear regression (MLR) and multicollinearity management for predictive model generation. It analyzes 541 articles from 1982 to 2023, highlighting steady annual growth and geographical distribution of research. The United States and China lead production, comprising 36.86% of documents. A growing trend in linear regression use within machine learning is observed. Applied research tackles multidisciplinary issues, primarily in social sciences. This study provides a detailed overview of current status, trends, and contributions in multicollinearity management in MLR models, emphasizing the importance of addressing this challenge for stable and valid predictive models.
AB - The bibliometric study addresses the scientific production employing multiple linear regression (MLR) and multicollinearity management for predictive model generation. It analyzes 541 articles from 1982 to 2023, highlighting steady annual growth and geographical distribution of research. The United States and China lead production, comprising 36.86% of documents. A growing trend in linear regression use within machine learning is observed. Applied research tackles multidisciplinary issues, primarily in social sciences. This study provides a detailed overview of current status, trends, and contributions in multicollinearity management in MLR models, emphasizing the importance of addressing this challenge for stable and valid predictive models.
KW - Machine learning
KW - Multicollinearity
KW - Multiple linear regression (MLR)
KW - Predictive models
KW - Scientific production
UR - https://www.scopus.com/pages/publications/105016201432
U2 - 10.1007/978-981-97-9324-2_29
DO - 10.1007/978-981-97-9324-2_29
M3 - Contribución a la conferencia
AN - SCOPUS:105016201432
SN - 9789819793235
T3 - Lecture Notes in Networks and Systems
SP - 355
EP - 371
BT - Intelligent Sustainable Systems - Selected Papers of WorldS4 2024
A2 - Nagar, Atulya
A2 - Jat, Dharm Singh
A2 - Mishra, Durgesh
A2 - Joshi, Amit
PB - Springer Science and Business Media Deutschland GmbH
Y2 - 23 July 2024 through 26 July 2024
ER -