Volume 16, Issue 2, June 2017, Pages 198 - 208
A New Bivariate Distribution Obtained by Compounding the Bivariate Normal and Geometric Distributions
Authors
Eisa Mahmoudi, Hamed Mahmoodian
Corresponding Author
Eisa Mahmoudi
Received 31 August 2016, Accepted 10 October 2016, Available Online 1 June 2017.
- DOI
- 10.2991/jsta.2017.16.2.5How to use a DOI?
- Keywords
- Normal distribution; Geometric distribution; EM algorithm; Maximum likelihood estimation.
- Abstract
Recently, Mahmoudi and Mahmoodian [7] introduced a new class of distributions which contains univariate normal–geometric distribution as a special case. This class of distributions are very flexible and can be used quite effectively to analyze skewed data. In this paper we propose a new bivariate distribution with the normal–geometric distribution marginals. Different properties of this new bivariate distribution have been studied. This distribution has five unknown parameters. The EM algorithm is used to determine the maximum likelihood estimates of the parameters. We analyze one series of real data set for illustrative purposes.
- Copyright
- © 2017, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - JOUR AU - Eisa Mahmoudi AU - Hamed Mahmoodian PY - 2017 DA - 2017/06/01 TI - A New Bivariate Distribution Obtained by Compounding the Bivariate Normal and Geometric Distributions JO - Journal of Statistical Theory and Applications SP - 198 EP - 208 VL - 16 IS - 2 SN - 2214-1766 UR - https://doi.org/10.2991/jsta.2017.16.2.5 DO - 10.2991/jsta.2017.16.2.5 ID - Mahmoudi2017 ER -