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.
| Autorius: | N. Balakrishna |
| Leidėjas: | Springer Nature Singapore |
| Išleidimo metai: | 2023 |
| Knygos puslapių skaičius: | 244 |
| ISBN-10: | 9811681643 |
| ISBN-13: | 9789811681646 |
| Formatas: | Knyga minkštu viršeliu |
| Kalba: | Anglų |
| Žanras: | Bayesian inference |
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