Unit root test
Arguments
- vintages.view
mts object. Vertical or diagonal view of the
create_vintages()
output- adfk
Number of lags to consider for Augmented Dicky-Fuller (ADF) test
- na.zero
Boolean whether missing values should be considered as 0 or rather as data not (yet) available (the default).
Examples
## Simulated data
df_long <- simulate_long(
n_period = 10L * 4L,
n_revision = 5L,
periodicity = 4L,
start_period = as.Date("2010-01-01")
)
## Create vintage and test
vintages <- create_vintages(df_long, periodicity = 4L)
unitroot(vintages$diagonal_view)
#> DF.value DF.stderr DF.statistic DF.pvalue ADF.value ADF.stderr
#> Release[1] 0.6933099 0.1059470 -2.894750 0.005289061 0.5888336 0.1135148
#> Release[2] 0.7418472 0.0964298 -2.677106 0.009192502 0.6606878 0.1049352
#> Release[3] 0.7779834 0.1144953 -1.939090 0.051188360 0.6541918 0.1152126
#> Release[4] 0.7796338 0.1083422 -2.033984 0.041652071 0.6703353 0.1159261
#> Release[5] 0.8237562 0.1151032 -1.531181 0.115846927 0.7255092 0.1273981
#> ADF.statistic ADF.pvalue DFCT.value DFCT.stderr DFCT.statistic
#> Release[1] -3.622140 0.000764028 0.459413830 0.1452405 -3.722008
#> Release[2] -3.233540 0.002183065 0.553793794 0.1382623 -3.227243
#> Release[3] -3.001479 0.004883293 0.275384339 0.2899485 -2.499118
#> Release[4] -2.843749 0.007020590 0.174248901 0.2994179 -2.757855
#> Release[5] -2.154591 0.032032024 -0.002920819 0.4047792 -2.477698
#> DFCT.pvalue PP.value PP.stderr PP.statistic PP.pvalue
#> Release[1] 0.03544964 0.6933099 0.1059470 -2.819899 0.006414345
#> Release[2] 0.09756964 0.7418472 0.0964298 -2.620522 0.010565924
#> Release[3] 0.34289464 0.7779834 0.1144953 -2.194692 0.029173749
#> Release[4] 0.23639116 0.7796338 0.1083422 -2.442588 0.016896947
#> Release[5] 0.35405329 0.8237562 0.1151032 -2.219585 0.027761251