1.

Record Nr.

UNINA9910299976303321

Autore

Turkman K. Feridun

Titolo

Non-Linear Time Series : Extreme Events and Integer Value Problems / / by Kamil Feridun Turkman, Manuel González Scotto, Patrícia de Zea Bermudez

Pubbl/distr/stampa

Cham : , : Springer International Publishing : , : Imprint : Springer, , 2014

ISBN

3-319-07028-2

Edizione

[1st ed. 2014.]

Descrizione fisica

1 online resource (255 p.)

Disciplina

330.015195

333.7

510

519.5

Soggetti

Statistics

Mathematics

Econometrics

Environmental sciences - Mathematics

Statistical Theory and Methods

Mathematical Applications in Environmental Science

Lingua di pubblicazione

Inglese

Formato

Materiale a stampa

Livello bibliografico

Monografia

Note generali

Description based upon print version of record.

Nota di bibliografia

Includes bibliographical references at the end of each chapters.

Nota di contenuto

1.Introduction -- 2.Nonlinear Time Series Models -- 3.Extremes of Nonlinear Time Series -- 4.Inference for Nonlinear Time Series Models -- 5.Models for Integer-valued Time Series.

Sommario/riassunto

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.