| 書目名稱 | Non-Parametric Statistical Diagnosis |
| 副標題 | Problems and Methods |
| 編輯 | B. E. Brodsky,B. S. Darkhovsky |
| 視頻video | http://file.papertrans.cn/667/666996/666996.mp4 |
| 叢書名稱 | Mathematics and Its Applications |
| 圖書封面 |  |
| 描述 | This book has a distinct philosophy and it is appropriate to make it explicit at the outset. In our view almost all classic statistical inference is based upon the assumption (explicit or implicit) that there exists a fixed probabilistic mechanism of data generation. Unlike classic statistical inference, this book is devoted to the statistical analysis of data about complex objects with more than one probabilistic mechanism of data generation. We think that the exis- tence of more than one data generation process (DGP) is the most important characteristic of com plex systems. When the hypothesis of statistical homogeneity holds true, Le., there exists only one mechanism of data generation, all statistical inference is based upon the fundamentallaws of large numbers. However, the situation is completely different when the probabilistic law of data generation can change (in time or in the phase space). In this case all data obtained must be ‘sorted‘ in subsamples generated by different probabilistic mechanisms. Only after such classification we can make correct inferences about all DGPs. There exists yet another type of problem for complex systems. Here it is important to detect poss |
| 出版日期 | Book 2000 |
| 關(guān)鍵詞 | biology; diagnosis; diagnostics; econometrics; statistics |
| 版次 | 1 |
| doi | https://doi.org/10.1007/978-94-015-9530-8 |
| isbn_softcover | 978-90-481-5465-4 |
| isbn_ebook | 978-94-015-9530-8 |
| copyright | Springer Science+Business Media Dordrecht 2000 |
|Archiver|手機版|小黑屋|
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