Title: Generalized discrete autoregressive moving-average models
Authors: Möller, Tobias 
Weiß, Christian H. 
Language: en
Keywords: Universitätsbibliographie;Evaluation 2020
Issue Date: 1-Jul-2020
Publisher: Wiley
Document Type: Article
Source: Enthalten in: Applied stochastic models in business and industry. - Chichester : Wiley, 1999. - Online-Ressource . - Bd. 36.2020, 4, Seite 641-659
Journal / Series / Working Paper (HSU): Applied stochastic models in business and industry 
Volume: 36
Issue: 4
Page Start: 641
Page End: 659
Publisher Place: Chichester
Abstract: 
© 2020 The Authors. Applied Stochastic Models in Business and Industry published by John Wiley & Sons, Ltd. This article proposes the generalized discrete autoregressive moving-average (GDARMA) model as a parsimonious and universally applicable approach for stationary univariate or multivariate time series. The GDARMA model can be applied to any type of quantitative time series. It allows to compute moment properties in a unique way, and it exhibits the autocorrelation structure of the traditional ARMA model. This great flexibility is obtained by using data-specific variation operators, which is illustrated for the most common types of time series data, such as counts, integers, reals, and compositional data. The practical potential of the GDARMA approach is demonstrated by considering a time series of integers regarding votes for a change of the interest rate, and a time series of compositional data regarding television market shares.
Organization Units (connected with the publication): Quantitative Methoden der Wirtschaftswissenschaften 
URL: https://ub.hsu-hh.de/DB=1/XMLPRS=N/PPN?PPN=1745188304
ISBN: 15264025
15264025
DOI: 10.1002/asmb.2520
Appears in Collections:2020

Show full item record

CORE Recommender

SCOPUSTM   
Citations

3
checked on May 18, 2022

Google ScholarTM

Check

Altmetric

Altmetric


Items in openHSU are protected by copyright, with all rights reserved, unless otherwise indicated.