We consider assortment and price optimization problems under the d-level nested logit model. In the assortment optimization problem, the goal is to find the revenue-maximizing assortment of products ...

Logistic regression is a powerful statistical method that is used to model the probability that a set of explanatory (independent or predictor) variables predict data in an outcome (dependent or ...

American Journal of Agricultural Economics, Vol. 85, No. 1 (Feb., 2003), pp. 248-253 (6 pages) Substantive income effects are incorporated in a logit or nested-logit model by assuming that utility is ...

eSpeaks host Corey Noles sits down with Qualcomm's Craig Tellalian to explore a workplace computing transformation: the rise of AI-ready PCs. Matt Hillary, VP of Security and CISO at Drata, details ...

"Logistic and Poisson Regression," Wednesday, November 5: The fourth LISA mini course focuses on appropriate model building for categorical response data, specifically binary and count data. The most ...