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Statistical Methods for Stochastic Differential Equations. 確率微分方程式のための統計方法
・ISBN 978-1-4398-4940-8 hard GB£ 145.99
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電子版あり 大学・学術機関向け電子ブック（eBook）ISBN 978-0-429-06325-1
| 著者・編者 | Kessler, Mathieu / Lindner, A. / Sorensen, M., |
|---|---|
| シリーズ | Chapman & Hall/CRC Monographs on Statistics & Applied Probability |
| 出版社 | (Chapman & Hall / CRC, US) |
| 出版年月 | 2012 |
| ページ数 | 508 pp. |
| 言語 | ENG |
| ニュース番号 | ＜588-280＞ |
解説
The seventh volume in the SemStat series, Statistical Methods for Stochastic Differential Equations presents current research trends and recent developments in statistical methods for stochastic differential equations. Written to be accessible to both new students and seasoned researchers, each self-contained chapter starts with introductions to the topic at hand and builds gradually towards discussing recent research.
The book covers Wiener-driven equations as well as stochastic differential equations with jumps, including continuous-time ARMA processes and COGARCH processes. It presents a spectrum of estimation methods, including nonparametric estimation as well as parametric estimation based on likelihood methods, estimating functions, and simulation techniques. Two chapters are devoted to high-frequency data. Multivariate models are also considered, including partially observed systems, asynchronous sampling, tests for simultaneous jumps, and multiscale diffusions.
Statistical Methods for Stochastic Differential Equations is useful to the theoretical statistician and the probabilist who works in or intends to work in the field, as well as to the applied statistician or financial econometrician who needs the methods to analyze biological or financial time series.