Abstract: A method of recommending products during e-commerce. A computing device including a processor implements a cross sampling recommender algorithm which includes a first statistical model is provided at a website. Responsive to receiving information via the Internet from a first customer including selection of a first product offered at the website, the algorithm automatically divides historical customer' selection information into a plurality of time ordered sub-periods of time. Using the customer' selection information and the time ordered sub-periods of time as a time covariate, logistic regressions are fit to each of a plurality of cross-sampled pairs of the plurality of products involving the first product. Using the data from the logistic regressions, cross-sampled pairs are identified which meet a slope selection criteria.

Abstract: A system for, and method of, generating a yield model pertaining to an integrated circuit (IC) fabrication process and a method of manufacturing an IC using the yield model. In one embodiment, the method of generating includes: (1) selecting X-variables as candidates for incorporation into the yield model, (2) sorting the candidates into an order based on a ranking criterion and (3) introducing the candidates in the order into a stepwise forward regression model until a marginal significance associated with a candidate to be introduced into the model falls below a threshold.