| 书目名称 | Stochastic Population Models |
| 副标题 | A Compartmental Pers |
| 编辑 | James H. Matis,Thomas R. Kiffe |
| 视频video | |
| 丛书名称 | Lecture Notes in Statistics |
| 图书封面 |  |
| 描述 | This monograph has been heavily influenced by two books. One is Ren shaw‘s [82] work on modeling biological populations in space and time. It was published as we were busily engaged in modeling African bee dispersal, and provided strong affirmation for the stochastic basis for our ecological modeling efforts. The other is the third edition of Jacquez‘ [28] classic book on compartmental analysis. He reviews stochastic compartmental analysis and utilizes generating functions in this edition to derive many useful re sults. We interpreted Jacquez‘ use of generating functions as a message that the day had come for modeling practioners to consider using this powerful approach as a model-building tool. We were inspired by the idea of using generating functions and related methods for two purposes. The first is to integrate seamlessly our previous research centering in stochastic com partmental modeling with our more recent research focusing on stochastic population modeling. The second, related purpose is to present some key research results of practical application in a natural, user-friendly way to the large user communities of compartmental and biological population modelers. One ge |
| 出版日期 | Book 2000 |
| 关键词 | Mathematica; Moment; bee; calculus; differential equation; equation; mathematical modeling; mathematical so |
| 版次 | 1 |
| doi | https://doi.org/10.1007/978-1-4612-1244-7 |
| isbn_softcover | 978-0-387-98657-9 |
| isbn_ebook | 978-1-4612-1244-7Series ISSN 0930-0325 Series E-ISSN 2197-7186 |
| issn_series | 0930-0325 |
| copyright | Springer Science+Business Media New York 2000 |
发表于 2025-3-21 16:33:25
