Volume 5, Issue 3, June 2012, Pages 472 - 482
On a Versatile Stochastic Growth Model
Authors
Samiur Arif, Ismail Khalil, Stephan Olariu
Corresponding Author
Samiur Arif
Received 8 February 2012, Accepted 14 February 2012, Available Online 1 June 2012.
- DOI
- 10.1080/18756891.2012.696911How to use a DOI?
- Keywords
- Stochastic Growth Models, Pure Birth Process, Time-Dependent Probabilities, Continuous Markov Chain
- Abstract
Growth phenomena are ubiquitous and pervasive not only in biology and the medical sciences, but also in economics, marketing and the computer and social sciences. We introduce a three-parameter version of the classic pure-birth process growth model when suitably instantiated, can be used to model growth phenomena in many seemingly unrelated application domains. We point out that the model is computationally attractive since it admits of conceptually simple, closed form solutions for the time-dependent probabilities.
- 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 - Samiur Arif AU - Ismail Khalil AU - Stephan Olariu PY - 2012 DA - 2012/06/01 TI - On a Versatile Stochastic Growth Model JO - International Journal of Computational Intelligence Systems SP - 472 EP - 482 VL - 5 IS - 3 SN - 1875-6883 UR - https://doi.org/10.1080/18756891.2012.696911 DO - 10.1080/18756891.2012.696911 ID - Arif2012 ER -