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Author
Tripathi Praveen Kumar (Dept. of Mathematics and Statistics, Banasthali Vidyapith, Rajasthan, India), Sen Rijji (Calcutta University), Upadhyay S.K. (Department of Statistics, Banaras Hindu University, Varanasi, India)
Title
A Bayes Algorithm for Model Compatibility and Comparisonof ARMA(p,q) Models
Source
Statistics in Transition, 2021, vol. 22, nr 2, s. 95-123, tab., wykr., bibliogr. 37 poz.
Keyword
Model ARMA, Produkt krajowy brutto (PKB), Prawdopodobieństwo, Statystyka
ARMA model, Gross domestic product (GDP), Probability, Statistics
Note
summ.
Abstract
The paper presents a Bayes analysis of an autoregressive-moving average model and its com-ponents based on exact likelihood and weak priors for the parameters where the priors aredefined so that they incorporate stationarity and invertibility restrictions naturally. A Gibbs-Metropolis hybrid scheme is used to draw posterior-based inferences for the models underconsideration. The compatibility of the models with the data is examined using the Ljung-Box-Pierce chi-square-based statistic. The paper also compares different compatible modelsthrough the posterior predictive loss criterion in order to recommend the most appropriateone. For a numerical illustration of the above, data on the Indian gross domestic productgrowth rate at constant prices are considered. Differencing the data once prior to conductingthe analysis ensured their stationarity. Retrospective short-term predictions of the data areprovided based on the final recommended model. The considered methodology is expectedto offer an easy and precise method for economic data analysis.(original abstract)
Accessibility
The Main Library of the Cracow University of Economics
The Library of Warsaw School of Economics
The Library of University of Economics in Katowice
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Bibliography
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ISSN
1234-7655
Language
eng
URI / DOI
http://dx.doi.org/10.21307/stattrans-2021-018
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