Tests for autocorrelation

Source: R/ac_test.R

  • 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)

Arguments

x

an ivx model or a numeric vector, usually the residuals from an ols regression.
lag

the number of lags.
order

lag TODO
type

the type of test statistic to be returned. Either "Chisq" for the Chi-squared test statistic or "F" for the F test statistic.
fill

starting values for the lagged residuals in the auxiliary regression. By default 0 but can also be set to NA.

Value

a numeric scalar or numeric vector.

Details

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.

See also

Box.test lmtest::bgtest

Examples


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***