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Non-gaussian autoregressive-type tim...

Balakrishna, N.

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 seriesby 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.
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$q(electronic bk.)

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$q(electronic bk.)

Standard No.: 10.1007/978-981-16-8162-2doiSubjects--Topical Terms:

181890
Time-series analysis.

LC Class. No.: QA280 / B35 2021

Dewey Class. No.: 519.55

Non-gaussian autoregressive-type time series
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505 0 $a 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.
520 $a 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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