Steve Weston

Provides a parallel backend for the %dopar% function using the Rmpi package.

Various tools for creating iterators, many patterned after functions in the Python itertools module, and others patterned after functions in the 'snow' package.

C5.0 decision trees and rule-based models for pattern recognition that extend the work of Quinlan (1993, ISBN:1-55860-238-0).

Misc functions for training and plotting classification and regression models.

One degree of freedom contrasts for 'lm', 'glm', 'gls', and 'geese' objects.

Regression modeling using rules with added instance-based corrections.

Provides a parallel backend for the %dopar% function using the multicore functionality of the parallel package.

Provides a parallel backend for the %dopar% function using the parallel package.

Support for the foreach looping construct. Foreach is an idiom that allows for iterating over elements in a collection, without the use of an explicit loop counter. This package in particular is intended to be used for its return value, rather than for its side effects. In that sense, it is similar to the standard lapply function, but doesn't require the evaluation of a function. Using foreach without side effects also facilitates executing the loop in parallel.

Support for iterators, which allow a programmer to traverse through all the elements of a vector, list, or other collection of data.

A novel tool for generating a piecewise constant estimation list of increasingly complex predictors based on an intensive and comprehensive search over the entire covariate space.

A set of functions that can be used to spatially thin species occurrence data. The resulting thinned data can be used in ecological modeling, such as ecological niche modeling.