InterUplift {tools4uplift}

Interaction estimator

Description

Fit the interaction uplift model estimator.

Usage

## S3 method for class 'formula'
InterUplift(formula, treat, data, ...)

## Default S3 method:
InterUplift(data, treat, outcome, predictors, input = "all", ...)

Arguments

data, formula

a data frame containing the treatment, the outcome and the predictors or a formula describing the model to be fitted.

treat

name of a binary (numeric) vector representing the treatment assignment (coded as 0/1).

outcome

name of a binary response (numeric) vector (coded as 0/1).

predictors

a vector of names representing the explanatory variables to include in the model.

input

an option for predictors argument. If "all" (default), the model assumes that the model has to create the interaction of all varibles with treat. If "best", the model assumes that the predictors vector is the output of the BestFeatures function.

...

additional arguments (other than formula, family, and data) to be passed to glm function for the interaction model.

Value

an interaction model

Author(s)

Mouloud Belbahri

References

Lo, V., S., Y. (2002) The true lift model: a novel data mining approach to response modeling in database marketing. ACM SIGKDD Explorations Newsletter, Vol. 4(2), 78-86.

Belbahri, M., Murua, A., Gandouet, O., and Partovi Nia, V. (2019) Uplift Regression, <https://dms.umontreal.ca/~murua/research/UpliftRegression.pdf>

Examples

library(tools4uplift)
data("SimUplift")

fit <- InterUplift(SimUplift, "treat", "y", colnames(SimUplift[, 3:12]))