| 書目名稱 | Testing for Random Walk Coefficients in Regression and State Space Models |
| 編輯 | Martin Moryson |
| 視頻video | http://file.papertrans.cn/904/903417/903417.mp4 |
| 叢書名稱 | Contributions to Statistics |
| 圖書封面 |  |
| 描述 | Regression and state space models with time varying coefficients are treated in a thorough manner. State space models are introduced as a means to model time varying regression coefficients. The Kalman filter and smoother recursions are explained in an easy to understand fashion. The main part of the book deals with testing the null hypothesis of constant regression coefficients against the alternative that they follow a random walk. Different exact and large sample tests are presented and extensively compared based on Monte Carlo studies, so that the reader is guided in the question which test to choose in a particular situation. Moreover, different new tests are proposed which are suitable in situations with autocorrelated or heteroskedastic errors. Additionally, methods are developed to test for the constancy of regression coefficients in situations where one knows already that some coefficients follow a random walk, thereby one is enabled to find out which of the coefficients varies over time. |
| 出版日期 | Book 1998 |
| 關(guān)鍵詞 | Econometrics; Estimator; Monte-Carlo Method; Monte-Carlo-Methode; Random-Walk Coefficients; Random-Walk-K |
| 版次 | 1 |
| doi | https://doi.org/10.1007/978-3-642-99799-0 |
| isbn_softcover | 978-3-7908-1132-2 |
| isbn_ebook | 978-3-642-99799-0Series ISSN 1431-1968 Series E-ISSN 2628-8966 |
| issn_series | 1431-1968 |
| copyright | Physica-Verlag Heidelberg 1998 |
|Archiver|手機版|小黑屋|
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