![]() If you want to use the ARIMA model specification or if the model includes an MA part, you could include as regressors in the linear model lags of the residuals obtained in a previous step, but it is easier to implement the test upon the residuals of the fitted ARIMA model: ar1 <- arima(y, order=c(1,0,0), xreg=xreg)īp.statistic <- (length(e) - df) * summary(fitaux)$r.squaredīp.pvalue <- pchisq(bp.statistic, df, lower. # lmtest::bptestreturns the Breusch and Pagan test statisticīe aware of the differences between the linear regression model and the specification of AR model with exogenous regressors. # alternatively the "dynlm" interface can be used Run Breusch-Pagan test with estat hettest. A small p-value, then, indicates that residual variance is non-constant (heteroscedastic). The Breusch-Pagan test regresses the residuals on the fitted values or predictors and checks whether they can explain any of the residual variance. Xreg <- as.matrix(datasource)įit1 <- lm(y ~ 0 + xreg + y) Use the Breusch-Pagan test to assess homoscedasticity. Example for an AR(1) model: y <- datasource Then you can use the function ncvTest in package car or bptest in package lmtest. If you are using an AR model, then you can fit it as a linear regression model where lags of the dependent variable are included as regressors (along with the other explanatory variables). I used the pysal package for this test but this function returns an error: import statsmodels.api as sm import pysal model sm.OLS (Y,X,missing 'drop') rs model. Some ideas on how to code or obtain the BP test statistic with an ARIMA model in R (the software that you are using according to your sample code): I used the statsmodels package to estimate my OLS regression. In this case, the BP test can be interesting in order to test whether there is a relationship between these regressors and the variance of the error. You did not mention it in the question but I noticed in the sample code that you are including exogenous regressors in the ARIMA model, X1.,X5. The purpose and interpretation of the test are nonetheless more appropriate in the context of a regression model rather than in a model for the autocorrelation structure of a time series model. Once you've clicked on the button, the dialog box appears. The values in Figure 1 can be achieved by placing the formulas. Setting up a homogeneity test of a time series After opening XLSTAT, click the Time button in the ribbon and select Homogeneity tests (see below). I don't see theoretical reasons that would invalidate the test in the context of an ARIMA model. BPagTest(R1, R2, chi) p-value of the Breusch-Pagan test for the X values in R1 and Y values in R2 if chi TRUE (default) then the chi-square test is used otherwise the F test is used. Is the BP test applicable to ARIMA models? (This question fits better within the scope of this site.) Your question makes me wonder why the Breusch-Pagan (BP) test is not available for the output from a fitted ARIMA model.
0 Comments
Leave a Reply. |