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What is the significance level of the portmanteau test?
You went on and tested the model for autocorrelation in the errors using a portmanteau test. The null hypothesis of no autocorrelation is rejected since the p-value of 0.002549 is lower than the significance level alpha of 0.05. Since autocorrelation is an undesirable feature you want to move on and search for a model with no autocorrelation.
When to use a portmanteau test in regression?
In the context of regression analysis, including regression analysis with time series structures, a portmanteau test has been devised, which allows a general test to be made for the possibility that a range of types nonlinear transformations of combinations of the explanatory variables should have been included in addition…
How is a portmanteau used in time series analysis?
In time series analysis, two well-known versions of a portmanteau test are available for testing for autocorrelation in the residuals of a model: it tests whether any of a group of autocorrelations of the residual time series are different from zero.
Is there a portmanteau test for ARIMA models?
This test is the Ljung–Box test, which is an improved version of the Box–Pierce test, having been devised at essentially the same time; a seemingly trivial simplification (omitted in the improved test) was found to have a deleterious effect. This portmanteau test is useful in working with ARIMA models.
How to return the portmanteau test and a test for dynamic stability?
Following functions are used to return the Portmanteau test and a test for dynamic stability (the last two rows): According to the AIC selection criteria, Lag 4 was proposed.
How to control serial independence with portmanteau test?
However, when we control for serial independence with the Portmanteau test, we find that only using Lag 3 (V.3) would remove the serial autocorrelation, as p-values > 0.1, i.e. 0.2. Okay, Lag 3 for now. Now I want to further control for “dynamic stability”, as proposed here.