Revisit the Wishart Distributionm
William Chen
International Journal of Statistics and Probability, 2020, vol. 9, issue 5, 79
Abstract:
If S_pxp can be written as S=X' X , where X_nxp is a data matrix from N_p(0,V) , then S is said to have a Wishart distribution with scale matrix V of degree of freedom parameter n. We write S~W_p(V,n). When V=I, the distribution is said to be in standard form. When p=1, the W_1(σ^2, n) distribution is found to be Σ^n_i=1(x^2_i) , where the elements of x_i are identically independently distributed unit normal variables; being the σ^2(x_n)^2 distribution. Although Anderson (1984, p248~249) has presented two theorems for the Wishart distribution. In the following we give an alternative proof.
Date: 2020
References: View complete reference list from CitEc
Citations:
Downloads: (external link)
http://www.ccsenet.org/journal/index.php/ijsp/article/download/0/0/43557/45707 (application/pdf)
http://www.ccsenet.org/journal/index.php/ijsp/article/view/0/43557 (text/html)
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:ibn:ijspjl:v:9:y:2020:i:5:p:79
Access Statistics for this article
More articles in International Journal of Statistics and Probability from Canadian Center of Science and Education Contact information at EDIRC.
Bibliographic data for series maintained by Canadian Center of Science and Education ().