A Comparison of Three Estimation Methods In Linear Regression Analysis
Available Online January 2017.
- 10.2991/icmmita-16.2016.92How to use a DOI?
- Linear Regression; Least Ordinary Square; Method of Moment; Maximum Likelihood Estimate; Hypothesis Testing; R-square
The paper begins with an introduction of some crucial definitions apropos of regression analysis. Then it discusses briefly the concept of R-square that verifies the accuracy of a regression model and of Hypothesis Testing that tests hypothesis made concerning the population. The main part of the paper then focuses on three estimation methods that estimate the parameters of a regression model: Ordinary Least Square, Method of Moments, and Maximum Likelihood Estimation. The paper concludes with a discussion on the advantages and disadvantages of each method and the possible applications of linear regression.
- © 2017, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - CONF AU - Xianghong Luo PY - 2017/01 DA - 2017/01 TI - A Comparison of Three Estimation Methods In Linear Regression Analysis BT - Proceedings of the 2016 4th International Conference on Machinery, Materials and Information Technology Applications PB - Atlantis Press SP - 498 EP - 502 SN - 2352-538X UR - https://doi.org/10.2991/icmmita-16.2016.92 DO - 10.2991/icmmita-16.2016.92 ID - Luo2017/01 ER -