Quick outlier treatment of a coin

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 coin
qTreat(
  x,
  dset,
  winmax = 5,
  skew_thresh = 2,
  kurt_thresh = 3.5,
  f2 = "log_CT",
  ...
)

Arguments

x

A coin

dset

Name of data set to treat for outliers

winmax

Maximum number of points to Winsorise for each indicator. 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.

Value

An updated coin with treated data set at .$Data$Treated.

Details

This function treats each indicator in the data set targeted by dset using the following process:

• First, it checks whether skew and kurtosis are within the specified limits of skew_thresh and kurt_thresh

• If the indicator is not within the limits, it applies the winsorise() function, with maximum number of winsorised points specified by winmax.

• If winsorisation does not bring the indicator within the skew/kurtosis limits, it is instead passed to f2, which is a second outlier treatment function, default log_CT().

The arguments of qTreat() are passed to Treat().

See Treat() documentation for more details, and vignette("treat").

Examples

# build example coin
coin <- build_example_coin(up_to = "new_coin", quietly = TRUE)

# treat with winmax = 3
coin <- qTreat(coin, dset = "Raw", winmax = 3)
#> Written data set to .$Data$Treated