Non-Gaussian Autoregressive-Type Time Series

Specificaties
Gebonden, blz. | Engels
Springer Nature Singapore | e druk, 2022
ISBN13: 9789811681615
Rubricering
Springer Nature Singapore e druk, 2022 9789811681615
Verwachte levertijd ongeveer 9 werkdagen

Samenvatting

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.

Specificaties

ISBN13:9789811681615
Taal:Engels
Bindwijze:gebonden
Uitgever:Springer Nature Singapore

Inhoudsopgave

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. 

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        Non-Gaussian Autoregressive-Type Time Series