Monitoring parameter change for bivariate time series models of counts.

J Korean Stat Soc

Department of Statistics, Seoul National University, Seoul, 08826 South Korea.

Published: May 2023

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Article Abstract

In this study, we consider an online monitoring procedure to detect a parameter change for bivariate time series of counts, following bivariate integer-valued generalized autoregressive heteroscedastic (BIGARCH) and autoregressive (BINAR) models. To handle this problem, we employ the cumulative sum (CUSUM) process constructed from the (standardized) residuals obtained from those models. To attain control limits, we develop limit theorems for the proposed monitoring process. A simulation study and real data analysis are conducted to affirm the validity of the proposed method.

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10164370PMC
http://dx.doi.org/10.1007/s42952-023-00212-9DOI Listing

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