Recently, variable selection by penalized likelihood has attracted much research interest. In this paper, we propose adaptive Lasso quantile regression (BALQR) from a Bayesian perspective. The method extends the Bayesian Lasso quantile regression by allowing different penalization parameters for...

The move towards a customer-centred approach to marketing, coupled with the increasing availability of customer transaction data, has led to an interest in understanding and estimating customer lifetime value (CLV). Several authors point out that, when evaluating customer profitability,...

In this article, we develop a Bayesian method for quantile regression in the case of dichotomous response data. The frequentist approach to this type of regression has proven problematic in both optimizing the objective function and making inference on the regression parameters. By accepting...

Currently, in order to remain competitive companies are adopting customer centered strategies and consequently customer relationship management (CRM) is gaining increasing importance. In this context, customer retention deserves particular attention. This paper proposes a model for partial churn...

Fierce competition as well as the recent financial crisis in financial and banking industries made credit scoring gain importance. An accurate estimation of credit risk helps organizations to decide whether or not to grant credit to potential customers. Many classification methods have been...