Linear regression model of the revisions (R) on a preliminary vintage (P)
Arguments
- vintages.view
mts object. Vertical or diagonal view of the
create_vintages()output- gap
Integer. Gap to consider between each vintages. Default is 1 which means that revisions are calculated and tested for each vintages consecutively.
- 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)
efficiencyModel1(vintages[["diagonal_view"]])
#> N R2 F intercept.estimate
#> [Release[2]]-[Release[1]] 19 0.01283303 0.2209975 0.1363549
#> [Release[3]]-[Release[2]] 16 0.12520114 2.0036787 -0.6855472
#> [Release[4]]-[Release[3]] 10 0.43472636 6.1524377 1.1451832
#> [Release[5]]-[Release[4]] 9 0.17219775 1.4561258 -0.3737869
#> intercept.stderr intercept.pvalue slope.estimate
#> [Release[2]]-[Release[1]] 0.9824646 0.89124803 -0.008101707
#> [Release[3]]-[Release[2]] 0.5235022 0.21143558 0.016423023
#> [Release[4]]-[Release[3]] 0.5124609 0.05588792 -0.046375895
#> [Release[5]]-[Release[4]] 0.2737676 0.21439928 0.012803985
#> slope.stderr slope.pvalue skewness kurtosis
#> [Release[2]]-[Release[1]] 0.01723387 0.64425529 1.3094666 1.6961203
#> [Release[3]]-[Release[2]] 0.01160217 0.17877773 0.3411671 -0.9031256
#> [Release[4]]-[Release[3]] 0.01869686 0.03808726 -0.5984240 -0.8518502
#> [Release[5]]-[Release[4]] 0.01061074 0.26674003 0.1664578 0.7157798
#> JarqueBera.value JarqueBera.pvalue BreuschPagan.R2
#> [Release[2]]-[Release[1]] 7.3017261 0.02596871 0.112040808
#> [Release[3]]-[Release[2]] 0.8007599 0.67006542 0.089780980
#> [Release[4]]-[Release[3]] 0.8092852 0.66721522 0.083332126
#> [Release[5]]-[Release[4]] 0.2077245 0.90134944 0.001005461
#> BreuschPagan.value BreuschPagan.pvalue White.R2
#> [Release[2]]-[Release[1]] 2.145023963 0.1612812 0.27543108
#> [Release[3]]-[Release[2]] 1.380913494 0.2595452 0.14994759
#> [Release[4]]-[Release[3]] 0.727261233 0.4185708 0.46234276
#> [Release[5]]-[Release[4]] 0.007045312 0.9354570 0.00263113
#> White.value White.pvalue arch.R2 arch.value
#> [Release[2]]-[Release[1]] 5.23319045 0.07305116 1.027382e-02 1.849288e-01
#> [Release[3]]-[Release[2]] 2.39916142 0.30132053 8.206081e-03 1.230912e-01
#> [Release[4]]-[Release[3]] 4.62342756 0.09909129 9.108695e-07 8.197826e-06
#> [Release[5]]-[Release[4]] 0.02368017 0.98822973 1.547083e-01 1.237666e+00
#> arch.pvalue
#> [Release[2]]-[Release[1]] 0.6671713
#> [Release[3]]-[Release[2]] 0.7257057
#> [Release[4]]-[Release[3]] 0.9977155
#> [Release[5]]-[Release[4]] 0.2659213