Automatic approach to obtain a relevance function for a given target variable when the option of extremes is chosen, i.e. users are more interested in accurately predicting extreme target values
phi.extremes(
y,
extr.type = c("both", "high", "low"),
coef = 1.5,
asym = TRUE,
...
)A list with three slots with information concerning the relevance function
The method used to generate the relevance function (extremes or range)
?
Three sets of values identifying the target value-relevance-derivate for the first low extreme value, the median, and first high extreme value
The target variable of a given data set
Type of extremes to be considered: low, high or both (default)
Boxplot coefficient (default 1.5)
Boolean for assymetric interpolation. Default TRUE, uses adjusted boxplot. When FALSE, uses standard boxplot.
Additional parameters