|
A two-sample multivariate test with one covariance matrix unknown |
|---|---|
| รหัสดีโอไอ | |
| Creator | 1. Samruam Chongcharoen 2. Manachai Rodchuen |
| Title | A two-sample multivariate test with one covariance matrix unknown |
| Publisher | Research and Development Office, Prince of Songkla University |
| Publication Year | 2564 |
| Journal Title | Songklanakarin Journal of Science an Technology (SJST) |
| Journal Vol. | 43 |
| Journal No. | 6 |
| Page no. | 1641-1647 |
| Keyword | approximate degrees of freedom, covariance matrix unknown, hypothesis testing, multivariate Behrensโ"Fisher problem, twoโ"sample multivariate test |
| URL Website | https://rdo.psu.ac.th/sjst/index.php |
| ISSN | 0125-3395 |
| Abstract | In this paper, we considered two-sample multivariate testing for testing the equality of two population mean vectors oftwo normal populations in this situation in which one covariance is assumed to be known and the other unknown when both thesample sizes are larger than their dimensions. We adapted a test statistic from Yao (1965) and developed its distribution. Theaccuracy of the proposed test is investigated by simulation study. Under simulation study, the simulated results showed that theattained significance levels of proposed tests are close to nominal significance level setting in every situation considered. Allproposed tests gave excellent performance and power in every situation considered except when the sample size from populationwith known covariance matrix is smaller than that from population with unknown covariance matrix. The two-sided proposedtest and the one-sided proposed test asH : a 1 2 ๏ญ ๏ญ ๏ผwork very well when the dimension is less than 30. Finally, we applied theproposed tests for analyzing the real data. |
