Non-Gaussian Autoregressive-Type Time Series
Title | Non-Gaussian Autoregressive-Type Time Series PDF eBook |
Author | N. Balakrishna |
Publisher | Springer Nature |
Pages | 238 |
Release | 2022-01-27 |
Genre | Mathematics |
ISBN | 9811681627 |
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.
Non-Gaussian First-order Autoregressive Time Series Models
Title | Non-Gaussian First-order Autoregressive Time Series Models PDF eBook |
Author | Leanna Marisa Tedesco |
Publisher | |
Pages | 274 |
Release | 1995 |
Genre | Autoregression (Statistics) |
ISBN |
Non-Linear Time Series
Title | Non-Linear Time Series PDF eBook |
Author | Kamil Feridun Turkman |
Publisher | Springer |
Pages | 255 |
Release | 2014-09-29 |
Genre | Mathematics |
ISBN | 3319070282 |
This book offers a useful combination of probabilistic and statistical tools for analyzing nonlinear time series. Key features of the book include a study of the extremal behavior of nonlinear time series and a comprehensive list of nonlinear models that address different aspects of nonlinearity. Several inferential methods, including quasi likelihood methods, sequential Markov Chain Monte Carlo Methods and particle filters, are also included so as to provide an overall view of the available tools for parameter estimation for nonlinear models. A chapter on integer time series models based on several thinning operations, which brings together all recent advances made in this area, is also included. Readers should have attended a prior course on linear time series, and a good grasp of simulation-based inferential methods is recommended. This book offers a valuable resource for second-year graduate students and researchers in statistics and other scientific areas who need a basic understanding of nonlinear time series.
Smoothing Non-Gaussian Time Series with Autoregressive Structure
Title | Smoothing Non-Gaussian Time Series with Autoregressive Structure PDF eBook |
Author | G. K. Grunwald |
Publisher | |
Pages | 23 |
Release | 1994 |
Genre | Nonparametric statistics |
ISBN |
Topics in Statistical Dependence
Title | Topics in Statistical Dependence PDF eBook |
Author | Henry W. Block |
Publisher | IMS |
Pages | 558 |
Release | 1990 |
Genre | Mathematical statistics |
ISBN | 9780940600232 |
Gaussian and Non-Gaussian Linear Time Series and Random Fields
Title | Gaussian and Non-Gaussian Linear Time Series and Random Fields PDF eBook |
Author | Murray Rosenblatt |
Publisher | Springer |
Pages | 0 |
Release | 2012-09-27 |
Genre | Mathematics |
ISBN | 9781461270676 |
The principal focus here is on autoregressive moving average models and analogous random fields, with probabilistic and statistical questions also being discussed. The book contrasts Gaussian models with noncausal or noninvertible (nonminimum phase) non-Gaussian models and deals with problems of prediction and estimation. New results for nonminimum phase non-Gaussian processes are exposited and open questions are noted. Intended as a text for gradutes in statistics, mathematics, engineering, the natural sciences and economics, the only recommendation is an initial background in probability theory and statistics. Notes on background, history and open problems are given at the end of the book.
Non-linear and Non-stationary Time Series Analysis
Title | Non-linear and Non-stationary Time Series Analysis PDF eBook |
Author | Maurice Bertram Priestley |
Publisher | |
Pages | 258 |
Release | 1988 |
Genre | Mathematics |
ISBN |