ac_test: For all tests
ac_test_wald: Wald test
ac_test_lb: Ljung-Box
ac_test_bp: Box-Pierce
ac_test_bg: Breusch-Godfrey
ac_test_wald(x, lag)
ac_test_lb(x, lag)
ac_test_bp(x, lag)
ac_test_bg(x, order, type, fill)an ivx model or a numeric vector, usually the residuals from an ols regression.
the number of lags.
lag TODO
the type of test statistic to be returned. Either "Chisq" for the Chi-squared test statistic or "F" for the F test statistic.
starting values for the lagged residuals in the auxiliary regression. By default 0 but can also be set to NA.
a numeric scalar or numeric vector.
If p-value < 0.051: You can reject the null hypothesis assuming a 5% chance of making a mistake. So you can assume that your values are showing dependence on each other.
Box.test lmtest::bgtest
mdl <- ivx(hpi ~ cpi + inv, data = ylpc)
ac_test_wald(mdl)
#> Lag Wald
#> 1 17.39***
ac_test(mdl)
#> Lag Wald LjungBox BoxPierce BreuschGodfrey
#> 1 17.39*** 42.56*** 41.83*** 46.73***
#> 2 45.31*** 57.45*** 56.38*** 46.94***
#> 3 47.96*** 99.86*** 97.57*** 70.99***
#> 4 82.82*** 155.5*** 151.3*** 82.14***
#> 5 91.79*** 176.6*** 171.6*** 82.31***