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Beschreibung
This book brings together a variety of non-Gaussian autoregressive-type models to analyze time-series data. This book collects and collates most of the available models in the field and provide their probabilistic and inferential properties. This book classifies the stationary time-series models into different groups such as linear stationary models with non-Gaussian innovations, linear stationary models with non-Gaussian marginal distributions, product autoregressive models and minification models. Even though several non-Gaussian time-series models are available in the literature, most of them are focusing on the model structure and the probabilistic properties.
Details
| Verlag | Springer Singapore |
| Ersterscheinung | 28. Januar 2022 |
| Maße | 23.5 cm x 15.5 cm |
| Gewicht | 535 Gramm |
| Format | Hardcover |
| ISBN-13 | 9789811681615 |
| Seiten | 225 |