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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]] 24  0.68520075 0.51299572  1.3356851 0.19472020
#> [Release[3]]-[Release[2]] 16 -0.53245504 0.22177933 -2.4008325 0.02977643
#> [Release[4]]-[Release[3]] 14  0.09985965 0.09404693  1.0618066 0.30765162
#> [Release[5]]-[Release[4]]  6  0.04276859 0.05596890  0.7641493 0.47926710
#>                                 ar(1) stderr.adjusted tstat.adjusted
#> [Release[2]]-[Release[1]]  0.37790842      0.76347841      0.8974723
#> [Release[3]]-[Release[2]]  0.18147355      0.26645061     -1.9983255
#> [Release[4]]-[Release[3]] -0.04636472      0.08978302      1.1122330
#> [Release[5]]-[Release[4]] -0.44250648      0.03479427      1.2291848
#>                           pvalue.adjusted
#> [Release[2]]-[Release[1]]      0.38897309
#> [Release[3]]-[Release[2]]      0.07080973
#> [Release[4]]-[Release[3]]      0.28314198
#> [Release[5]]-[Release[4]]      0.23730793