An Asymptotic Two-Sided Test in a Family of Multivariate Distribution
- https://doi.org/10.2991/jsta.d.200511.001How to use a DOI?
- Asymptotic two-sided test, Chi-squared distribution, Efficient algorithm, Multivariate distribution elements
In the present paper, a two-sided test in a family of multivariate distribution according to the Mahalanobis distance with mean vector and positive definite matrix is considered. First, a family of multivariate distribution is introduced, then using the likelihood ratio method a test statistic is computed. The distribution of the test statistic is proposed for different sample sizes and fixed dimension. We study the distribution approximation computed using the likelihood ratio test and an efficient algorithm to compute the density functions can be derived according to Witkovsk´y, J. Stat. Plan. Inference. 94 (2001), 1–13. Also, a simulation study is presented on the sample sizes and powers to compare the performance of tests and show that the proposed distribution approximation is better than the classical distribution approximation.
- © 2020 The Authors. Published by Atlantis Press SARL.
- Open Access
- This is an open access article distributed under the CC BY-NC 4.0 license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - JOUR AU - Abouzar Bazyari AU - Mahmoud Afshari AU - Monjed H. Samuh PY - 2020 DA - 2020/05 TI - An Asymptotic Two-Sided Test in a Family of Multivariate Distribution JO - Journal of Statistical Theory and Applications SN - 2214-1766 UR - https://doi.org/10.2991/jsta.d.200511.001 DO - https://doi.org/10.2991/jsta.d.200511.001 ID - Bazyari2020 ER -