Parallel Algorithms for Linear Models provides a complete and detailed account of the design, analysis and implementation of parallel algorithms for solving large-scale linear models. It investigates and presents efficient, numerically stable algorithms for computing the least-squares estimators...

Optimal response modeling is studied using logistic regression, random forests, and I* algorithm of building tuned regressions. Transforming categorical variables into either WOE (weight of evidence) or probability of response coupled with equal frequency binning of size 10 results in improved...

A new 3-dimensional interpolation method is introduced in this paper. Corresponding to the method a novel interpolation operator has been constructed and used to obtain results. The main objective is to develop a mechanical way of interpolation that does not require very high degree of knowledge...

In this article, a simple algorithm is provided to maximize a family of optimal statistics for hypothesis testing with a nuisance parameter not defined under the null hypothesis. This arises from genetic linkage and association studies and other hypothesis testing problems. It is known that the...