Mapping an uncertainty zone between interpolated types of a categorical variable

Categorical data cannot be interpolated directly because they are outcomes of discrete random variables. Thus, types of categorical variables are transformed into indicator functions that can be handled by interpolation methods. Interpolated indicator values are then backtransformed to the original types of categorical variables. However, aspects such as variability and uncertainty of interpolated values of categorical data have never been considered. In this paper we show that the interpolation variance can be used to map an uncertainty zone around boundaries between types of categorical variables. Moreover, it is shown that the interpolation variance is a component of the total variance of the categorical variables, as measured by the coefficient of unalikeability.

► We propose a method to map uncertainty zone of interpolated categorical variable. ► We transform categorical variable types into indicator functions for interpolation. ► Interpolation variance (InV) can be used to map the uncertainty zone. ► InV is a component of total variance, as measured by coefficient of unalikeability.