Patent Document ID: 9361274
Application ID: 13793724
Patent Status: 1

Claim One:
1. A computer program product, the computer program product comprising a computer readable storage medium having program code embodied therewith, the program code executable by at least one processor to: calculate, by the at least one processor, basic statistics for a pair of categorical predictor variables and a target variable from a dataset during a single pass over the dataset, wherein the basic statistics include a number of categories for a first categorical predictor variable of the pair and a number of categories for a second categorical predictor variable of the pair, and wherein the target variable is associated with a purchase decision; and determine, by the at least one processor, that there are significant interaction effects for the pair of categorical predictor variables on the target variable based on a pattern by: calculating, by the at least one processor, a log-likelihood value for a full generalized linear model without estimating model parameters; calculating, by the at least one processor, the model parameters for a reduced generalized linear model with a recursive marginal mean accumulation technique using the basic statistics based on the single pass over the dataset; calculating, by the at least one processor, a log-likelihood value for the reduced generalized linear model; calculating, by the at least one processor, a likelihood ratio test statistic using the log-likelihood value for the full generalized linear model and the log-likelihood value for the reduced generalized linear model; calculating, by the at least one processor, a p-value of the likelihood ratio test statistic; and comparing, by the at least one processor, the p-value to a significance level; and output the significant interaction effects for the pair of categorical predictor variables on the target variable in a list for subsequent analyses to determine a behavior of the purchase decision.