Name
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. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1080/18756891.2012.696911 | INTERNATIONAL JOURNAL OF COMPUTATIONAL INTELLIGENCE SYSTEMS |
Keywords | DocType | Volume |
Stochastic Growth Models, Pure Birth Process, Time-Dependent Probabilities, Continuous Markov Chain | Journal | 5 |
Issue | ISSN | Citations |
3 | 1875-6891 | 2 |
PageRank | References | Authors |
0.46 | 6 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Samiur Arif | 1 | 57 | 3.78 |
| Ismail Khalil | 2 | 117 | 11.30 |
| Stephan Olariu | 3 | 2252 | 166.46 |