Journal of Mathematics Research
The Analysis of Bootstrap Method in Linear Regression Effect
Abstract
This paper combines the least squaress estimate, least absolute deviation estimate, least median estimate with Bootstrap
method. When the overall error distribution is unknown or it is not the normal distribution, we estimate the regression coefficient
and confidence interval of coefficient, and through data simulation, obtain Bootstrap method, which can improve
stability of regression coefficient and reduce the length of confidence interval.
method. When the overall error distribution is unknown or it is not the normal distribution, we estimate the regression coefficient
and confidence interval of coefficient, and through data simulation, obtain Bootstrap method, which can improve
stability of regression coefficient and reduce the length of confidence interval.
This work is licensed under a Creative Commons Attribution 3.0 License.
Journal of Mathematics Research ISSN 1916-9795 (Print) ISSN 1916-9809 (Online)
Copyright © Canadian Center of Science and Education
To make sure that you can receive messages from us, please add the 'ccsenet.org' domain to your e-mail 'safe list'. If you do not receive e-mail in your 'inbox', check your 'bulk mail' or 'junk mail' folders.