European University Institute Library

Non-Gaussian Autoregressive-Type Time Series, by N. Balakrishna

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.--, Provided by publisher
Table Of Contents
1. Basics of Time Series -- 2. Statistical Inference for Stationary Time Series -- 3. AR Models with Stationary Non-Gaussian Positive Marginals -- 4. AR Models with Stationary Non-Gaussian Real-Valued Marginals -- 5. Some Nonlinear AR-type Models for Non-Gaussian Time series -- 6. Linear Time Series Models with Non-Gaussian Innovations -- 7. Autoregressive-type Time Series of Counts.
Literary Form
non fiction
1st ed. 2021.
Physical Description
1 online resource (XVIII, 225 pages)
Specific Material Designation
Form Of Item


Library Locations

  • Badia Fiesolana

    Via dei Roccettini 9, San Domenico di Fiesole, 50014, IT