Non-Gaussian Autoregressive-Type Time Series
Author | : N. Balakrishna |
Publisher | : Springer Nature |
Total Pages | : 238 |
Release | : 2022-01-27 |
ISBN-10 | : 9789811681622 |
ISBN-13 | : 9811681627 |
Rating | : 4/5 (22 Downloads) |
Book excerpt: 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.