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] 1.0328634 0.07377414 0.4454601 0.8011735 1.061959 0.08698220
#> Release[2] 1.0615015 0.07152490 0.8598613 0.8898221 1.063526 0.08027818
#> Release[3] 1.1812444 0.15000615 1.2082466 0.9369958 1.172373 0.18283643
#> Release[4] 0.6664229 0.38438941 -0.8678102 0.3169076 1.148419 NaN
#> Release[5] 0.0000000 0.00000000 0.0000000 0.0000000 0.000000 0.00000000
#> ADF.statistic ADF.pvalue DFCT.value DFCT.stderr DFCT.statistic
#> Release[1] 0.7123188 0.8625823 0.02087265 0.2356117 -4.155682
#> Release[2] 0.7913275 0.8776692 0.19382245 0.2416421 -3.336247
#> Release[3] 0.9427727 0.9025676 0.10492444 0.3778558 -2.368829
#> Release[4] NaN NaN -2.48545171 NaN NaN
#> Release[5] 0.0000000 0.0000000 0.00000000 0.0000000 0.000000
#> DFCT.pvalue PP.value PP.stderr PP.statistic PP.pvalue
#> Release[1] 0.01774043 1.0328634 0.07377414 1.0795272 0.9225114
#> Release[2] 0.08614630 1.0615015 0.07152490 1.3952913 0.9551763
#> Release[3] 0.40523727 1.1812444 0.15000615 1.3147827 0.9475635
#> Release[4] NaN 0.6664229 0.38438941 -0.8704289 0.3159075
#> Release[5] 0.00000000 0.0000000 0.00000000 0.0000000 0.0000000