Churn {bayesQR}R Documentation

Customer Churn Data

Description

This dataset is a stratified random sample from all active customers (at the end of June 2006) of a European financial services company. The dependent variable in this dataset is the churn behavior of the customers in the period from July 1st until December 31th 2006. Here a churned customer is defined as someone who closed all his/her bank accounts with the company. Note that all predictor variables are standardized. This dataset is a small subset of the dataset used in Benoit and Van den Poel (2013). The dataset is structured as a dataframe with 400 observations and 5 variables.

Usage

data("Churn")

Format

The data frame has the following components:

Source

Benoit, D.F. and Van den Poel, D. (2013). Quantile regression for database marketing: methods and applications. In: Coussement, K., De Bock, K.W. and Neslin, S.A. (eds.). Advanced database marketing: Innovative methodologies and applications for managing customer relationships. Gower Publishing: London (UK). <doi:10.4324/9781315565682>

References

Benoit, D.F. and Van den Poel, D. (2013). Quantile regression for database marketing: methods and applications. In: Coussement, K., De Bock, K.W. and Neslin, S.A. (eds.). Advanced database marketing: Innovative methodologies and applications for managing customer relationships. Gower Publishing: London (UK). <doi:10.4324/9781315565682>

Benoit, D.F and Van den Poel, D. (2017). bayesQR: A Bayesian Approach to Quantile Regression, Journal of Statistical Software, 76(7), 1-32. <doi:10.18637/jss.v076.i07>


[Package bayesQR version 2.3 Index]