Exact bootstrap confidence intervals for regression coefficients in small samples |
| |
| Authors: | Klairung Samart Naratip Jansakul Mitchai Chongcheawchamnan |
| |
| Affiliation: | 1. Department of Mathematics and Statistics, Faculty of Science, Prince of Songkla University, Songkhla, Thailandklairung.s@psu.ac.th;3. Department of Mathematics and Statistics, Faculty of Science, Prince of Songkla University, Songkhla, Thailand;4. Department of Electrical Engineering, Faculty of Engineering, Prince of Songkla University, Songkhla, Thailand |
| |
| Abstract: | ABSTRACTRegression analysis is one of the important tools in statistics to investigate the relationships among variables. When the sample size is small, however, the assumptions for regression analysis can be violated. This research focuses on using the exact bootstrap to construct confidence intervals for regression parameters in small samples. The comparison of the exact bootstrap method with the basic bootstrap method was carried out by a simulation study. It was found that on a very small sample (n ≈ 5) under Laplace distribution with the independent variable treated as random, the exact bootstrap was more effective than the standard bootstrap confidence interval. |
| |
| Keywords: | Confidence intervals Exact bootstrapping Regression analysis Small dataset |
|
|
