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Non-Gaussian Autoregressive-Type Tim...
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Non-Gaussian Autoregressive-Type Time Series
Record Type:
Language materials, printed : Monograph/item
Title/Author:
Non-Gaussian Autoregressive-Type Time Series/ by N. Balakrishna.
Author:
Balakrishna, N.
Description:
XVIII, 225 p.online resource. :
Contained By:
Springer Nature eBook
Subject:
Time-series analysis. -
Online resource:
https://doi.org/10.1007/978-981-16-8162-2
ISBN:
9789811681622
Non-Gaussian Autoregressive-Type Time Series
Balakrishna, N.
Non-Gaussian Autoregressive-Type Time Series
[electronic resource] /by N. Balakrishna. - 1st ed. 2021. - XVIII, 225 p.online resource.
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. .
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.
ISBN: 9789811681622
Standard No.: 10.1007/978-981-16-8162-2doiSubjects--Topical Terms:
528412
Time-series analysis.
LC Class. No.: QA280
Dewey Class. No.: 519.55
Non-Gaussian Autoregressive-Type Time Series
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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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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.
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Mathematics and Statistics (R0) (SpringerNature-43713)
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