We predict the onset of personal bankruptcy using least squares regression. Although well publicized, only 2,244 bankruptcies occur in our data set of 2.9 million months of credit-card activity. We use stepwise selection to find predictors of these from a mix of payment history, debt load, demographics, and their interactions. This combination of rare responses and over 67,000 possible predicto...

We predict the onset of personal bankruptcy using least squares regression. Although well publicized, only 2,244 bankruptcies occur in our data set of 2.9 million months of credit-card activity. We use stepwise selection to find predictors from a mix of payment history, debt load, demographics, and their interactions. This combination of rare responses and over 67,000 possible predictors leads ...

Multiple regression approach has been used to forecast the crop production widely. This study undertaken evaluate performance of stepwise and Lasso (Least absolute shrinkage selection operator) technique in variable development wheat model for yield using weather data period 1984-2015, collected from IARI, New Delhi. Statistical parameters viz. R2, RMSE, MAPE were 0.81, 195.90 4.54 per cent res...

Multiple regression is a powerful set of methods for examining specific scientific hypotheses and relationships among experimental, quasiexperimental, and nonexperimental data. Typically, multiple regression is used as a data-analytic strategy to explain or predict a criterion (dependent) variable with a set of predictor (independent) variables. Wampold and Freund (1987) provided an important a...

The profit resulting from customer relationship is essential to ensure companies viability, so an improvement in customer retention is crucial for competitiveness. As such, companies have recognized the importance of customer centered strategies and consequently customer relationship management (CRM) is often at the core of their strategic plans. In this context, a priori knowledge about the ri...