<電子ブック>
Non-Gaussian Autoregressive-Type Time Series / by N. Balakrishna
版 | 1st ed. 2021. |
---|---|
出版者 | Singapore : Springer Nature Singapore : Imprint: Springer |
出版年 | 2021 |
大きさ | XVIII, 225 p : online resource |
著者標目 | *Balakrishna, N author SpringerLink (Online service) |
件 名 | LCSH:Time-series analysis LCSH:Statistics FREE:Time Series Analysis FREE:Bayesian Inference FREE:Statistics |
一般注記 | 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 HTTP:URL=https://doi.org/10.1007/978-981-16-8162-2 |
目次/あらすじ
所蔵情報を非表示
電子ブック | 配架場所 | 資料種別 | 巻 次 | 請求記号 | 状 態 | 予約 | コメント | ISBN | 刷 年 | 利用注記 | 指定図書 | 登録番号 |
---|---|---|---|---|---|---|---|---|---|---|---|---|
電子ブック | オンライン | 電子ブック |
|
|
Springer eBooks | 9789811681622 |
|
電子リソース |
|
EB00201246 |