Linear regression model of a latter vintage (L) 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)
slope_and_drift(vintages[["diagonal_view"]])
#> N R2 F intercept.estimate intercept.stderr
#> Release[2] 30 0.9582096 642.0096 2.38012100 1.0109255
#> Release[3] 29 0.9877298 2173.4588 0.09727184 0.6110874
#> Release[4] 27 0.9970934 8575.9841 -0.09147092 0.3134805
#> Release[5] 7 0.9987433 3973.7494 -0.07546477 0.2618083
#> intercept.pvalue slope.estimate slope.stderr slope.pvalue skewness
#> Release[2] 0.02579832 0.9158434 0.03614518 0.02734305 -0.1103667
#> Release[3] 0.87471316 1.0058199 0.02157469 0.78939966 -0.7141803
#> Release[4] 0.77285373 0.9983005 0.01078001 0.87600007 -0.1302344
#> Release[5] 0.78472634 0.9983556 0.01583744 0.92134195 0.3942945
#> kurtosis JarqueBera.value JarqueBera.pvalue BreuschPagan.R2
#> Release[2] -0.2758592 0.1508260 0.9273604 0.005063969
#> Release[3] 0.3052164 2.4889330 0.2880946 0.022796382
#> Release[4] -0.9212259 0.9928762 0.6086949 0.078338705
#> Release[5] -2.0722253 1.2289976 0.5409119 0.006901294
#> BreuschPagan.value BreuschPagan.pvalue White.R2 White.value
#> Release[2] 0.14251281 0.7086421 0.11607410 3.48222286
#> Release[3] 0.62986087 0.4343262 0.09507711 2.75723624
#> Release[4] 2.12493206 0.1573676 0.09411348 2.54106406
#> Release[5] 0.03474626 0.8594553 0.01384836 0.09693853
#> White.pvalue arch.R2 arch.value arch.pvalue
#> Release[2] 0.1753254 0.034419904 0.9981772 0.3177520
#> Release[3] 0.2519264 0.003325625 0.0931175 0.7602507
#> Release[4] 0.2806823 0.045597249 1.1855285 0.2762334
#> Release[5] 0.9526866 0.236467682 1.4188061 0.2336000