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Estimate bias using t-test and augmented t-test

Source: R/tests.R
bias.Rd

Estimate bias using t-test and augmented t-test

Usage

bias(revisions.view, na.zero = FALSE)

Arguments

revisions.view

mts object. Vertical or diagonal view of the get_revisions() output

na.zero

Boolean whether missing values should be considered as 0 or rather as data not (yet) available (the default).

See also

revision_analysis(), render_report()

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 = 4)
revisions <- get_revisions(vintages, gap = 1)
bias(revisions[["diagonal_view"]])
#>                            N    estimate    stderr      tstat    pvalue
#> [Release[2]]-[Release[1]] 28 -0.41501583 0.3493686 -1.1879026 0.2452168
#> [Release[3]]-[Release[2]] 24  0.13813280 0.2511954  0.5499017 0.5876876
#> [Release[4]]-[Release[3]] 21 -0.02999737 0.1640410 -0.1828651 0.8567449
#> [Release[5]]-[Release[4]]  6 -0.01251869 0.1212942 -0.1032093 0.9218086
#>                                 ar(1) stderr.adjusted tstat.adjusted
#> [Release[2]]-[Release[1]]  0.04507499      0.36548784     -1.1355120
#> [Release[3]]-[Release[2]] -0.23610716      0.19746943      0.6995148
#> [Release[4]]-[Release[3]] -0.19036531      0.13528724     -0.2217309
#> [Release[5]]-[Release[4]] -0.27470527      0.09149398     -0.1368253
#>                           pvalue.adjusted
#> [Release[2]]-[Release[1]]       0.2666867
#> [Release[3]]-[Release[2]]       0.4883993
#> [Release[4]]-[Release[3]]       0.8259834
#> [Release[5]]-[Release[4]]       0.8937461