Document Type
Article
Publication Date
2014
DOI
10.6000/1929-6029.2014.03.02.2
Publication Title
International Journal of Statistics in Medical Research
Volume
3
Issue
2
Pages
88-93
Abstract
Recent advances in computer modeling allows us to find closer fits to data. Our emphasis is on the interdependence between occurrence at kidney dialysis. The interdependence between kidney dialysis occurrences is modelled by a bivariate exponential that we propose in this article. The application is shown on the McGilchrist and Aisbett kidney data set with the use of the exponential distribution. The proposed bivariate exponential model has exponential marginal densities, correlated via a latent random variables and with finite probability of simultaneous occurrence. Extension of the model to a bivariate Erlang type distribution with same shape parameter is presented.
Rights
© 2014 Norou Diawara, S.H. Sathish Indika, Melva Grant, Edgard M. Maboudou-Tchao.
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0) License.
Original Publication Citation
Diawara, N., Indika, S. S., Grant, M., & Maboudou-Tchao, E. M. (2014). The bivariate erlang and its application in modeling recurrence times of kidney dialysis data. International Journal of Statistics in Medical Research, 3(2), 88-93. https://doi.org/10.6000/1929-6029.2014.03.02.2
ORCID
0000-0002-8403-6793 (Diawara), 0000-0001-5396-0732 (Grant)
Repository Citation
Diawara, Norou; Indika, S.H. Sathish; Grant, Melva; and Maboudou-Tchao, Edgard M., "The Bivariate Erlang and Its Application in Modeling Recurrence Times of Kidney Dialysis Data" (2014). Mathematics & Statistics Faculty Publications. 231.
https://digitalcommons.odu.edu/mathstat_fac_pubs/231