In this study, the residuals in time series analysis, which were classified in four different classes as ”conditional residuals”, ”unconditional residuals”, ”innovation” and ”normalized residuals”, are calculated by a simulation study for the ARMA model under certain parameter values for different numbers of observation and their conditions in diagnostic checking are examined using the test statistic which belongs to Ljung Box
📌 3 Key Takeaways
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Objective & Hypothesis:In this study, the residuals in time series analysis, which were classified in four different classes as ”conditional residuals”, ”unconditional residuals”, ”innovation” and ”normalized residuals”, are calculated by a simulation study for the ARMA model under certain parameter values for different numbers of observation and their conditions in diagnostic checking are examined using the test statistic which belongs to Ljung Box
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Key Findings & Data:In this study, the residuals in time series analysis, which were classified in four different classes as ”conditional residuals”, ”unconditional residuals”, ”innovation” and ”normalized residuals”, are calculated by a simulation study for the ARMA model under certain parameter values for different numbers of observation and their conditions in diagnostic checking are examined using the test statistic which belongs to Ljung Box
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Conclusion & Impact:In this study, the residuals in time series analysis, which were classified in four different classes as ”conditional residuals”, ”unconditional residuals”, ”innovation” and ”normalized residuals”, are calculated by a simulation study for the ARMA model under certain parameter values for different numbers of observation and their conditions in diagnostic checking are examined using the test statistic which belongs to Ljung Box
In this study, the residuals in time series analysis, which were classified in four different classes as ”conditional residuals”, ”unconditional residuals”, ”innovation” and ”normalized residuals”, are calculated by a simulation study for the ARMA model under certain parameter values for different numbers of observation and their conditions in diagnostic checking are examined using the test statistic which belongs to Ljung Box
UNSAL, M. G., KASAP, R. (2022). Cases of residual types in diagnostic checking for ARMA model. Hacettepe Journal of Mathematics and Statistics, Cilt: 43 - Sayı: 3, 543–552. https://ajindex.com/articles/530356