A simplified version of Treat()
which allows direct access to the default parameters. This has less flexibility,
but is an easier interface and probably more convenient if the objective is to use the default treatment process
but with some minor adjustments.
Usage
# S3 method for class 'data.frame'
qTreat(x, winmax = 5, skew_thresh = 2, kurt_thresh = 3.5, f2 = "log_CT", ...)
Arguments
- x
A numeric data frame
- winmax
Maximum number of points to Winsorise for each column. Default 5.
- skew_thresh
Absolute skew threshold - default 2.
- kurt_thresh
Kurtosis threshold - default 3.5.
- f2
Function to call if Winsorisation does not bring skew and kurtosis within limits. Default
"log_CT"
.- ...
arguments passed to or from other methods.
Details
This function treats each column in x
using the following process:
First, it checks whether skew and kurtosis are within the specified limits of
skew_thresh
andkurt_thresh
If the column is not within the limits, it applies the
winsorise()
function, with maximum number of winsorised points specified bywinmax
.If winsorisation does not bring the column within the skew/kurtosis limits, it is instead passed to
f2
, which is a second outlier treatment function, defaultlog_CT()
.
The arguments of qTreat()
are passed to Treat()
.
See Treat()
documentation for more details, and vignette("treat")
.
Examples
# select three indicators
df1 <- ASEM_iData[c("Flights", "Goods", "Services")]
# treat data frame, changing winmax and skew/kurtosis limits
l_treat <- qTreat(df1, winmax = 1, skew_thresh = 1.5, kurt_thresh = 3)
# Now we check what the results are:
l_treat$Dets_Table
#> iCode check_SkewKurt0.Pass check_SkewKurt0.Skew check_SkewKurt0.Kurt
#> 1 Flights FALSE 2.103287 4.508879
#> 2 Goods FALSE 2.649973 8.266610
#> 3 Services TRUE 1.701085 2.375656
#> winsorise.nwin check_SkewKurt1.Pass check_SkewKurt1.Skew check_SkewKurt1.Kurt
#> 1 1 FALSE 1.900658 3.336065
#> 2 1 FALSE 2.469910 7.087309
#> 3 NA NA NA NA
#> check_SkewKurt2.Pass check_SkewKurt2.Skew check_SkewKurt2.Kurt
#> 1 TRUE -0.09502644 -0.8305217
#> 2 TRUE 0.03104001 -0.8888965
#> 3 NA NA NA