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[ subject:"Time Series Analysis." ]
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Non-gaussian autoregressive-type tim...
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Balakrishna, N.
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Non-gaussian autoregressive-type time series
紀錄類型:
書目-電子資源 : Monograph/item
正題名/作者:
Non-gaussian autoregressive-type time series/ by N. Balakrishna.
作者:
Balakrishna, N.
出版者:
Singapore :Springer Singapore : : 2021.,
面頁冊數:
1 online resource (xviii, 225 p.) :ill., digital ;24 cm.
內容註:
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.
Contained By:
Springer Nature eBook
標題:
Time-series analysis. -
電子資源:
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. - Singapore :Springer Singapore :2021. - 1 online resource (xviii, 225 p.) :ill., digital ;24 cm.
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:
532530
Time-series analysis.
LC Class. No.: QA280 / B35 2021
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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