| 書目名稱 | Statistical Inference for Spatial Poisson Processes |
| 編輯 | Yu. A. Kutoyants |
| 視頻video | http://file.papertrans.cn/877/876441/876441.mp4 |
| 叢書名稱 | Lecture Notes in Statistics |
| 圖書封面 |  |
| 描述 | This work is devoted to several problems of parametric (mainly) and nonparametric estimation through the observation of Poisson processes defined on general spaces. Poisson processes are quite popular in applied research and therefore they attract the attention of many statisticians. There are a lot of good books on point processes and many of them contain chapters devoted to statistical inference for general and partic- ular models of processes. There are even chapters on statistical estimation problems for inhomogeneous Poisson processes in asymptotic statements. Nevertheless it seems that the asymptotic theory of estimation for nonlinear models of Poisson processes needs some development. Here nonlinear means the models of inhomogeneous Pois- son processes with intensity function nonlinearly depending on unknown parameters. In such situations the estimators usually cannot be written in exact form and are given as solutions of some equations. However the models can be quite fruitful in en- gineering problems and the existing computing algorithms are sufficiently powerful to calculate these estimators. Therefore the properties of estimators can be interesting too. |
| 出版日期 | Book 1998 |
| 關(guān)鍵詞 | Estimator; Likelihood; Poisson process; Probability theory; Stochastic processes; mathematical statistics |
| 版次 | 1 |
| doi | https://doi.org/10.1007/978-1-4612-1706-0 |
| isbn_softcover | 978-0-387-98562-6 |
| isbn_ebook | 978-1-4612-1706-0Series ISSN 0930-0325 Series E-ISSN 2197-7186 |
| issn_series | 0930-0325 |
| copyright | Springer Science+Business Media New York 1998 |
|Archiver|手機版|小黑屋|
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