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...the crossproducts are solved by using a sweep algorithm (Goodnight 1979). The method is accurate for data that are reasonably scaled and not too collinear. The sweep algorithm is also used in many places in the model-selection methods and the RSQUARE method uses the leaps-and-bounds algorithm by Furnival and Wilson (1974). Thanks. Thanks. CZ -- View this message in context: http://r.789695.n4.nabble.com/Does-R-have-function-package-works-similar-to-SAS-s-PROC-REG-tp2965657p2965657.html Sent from the R help mailing list archive at Nabble.com.

Version 0.9-99 of package "subselect" is now on CRAN. The subselect package has functions that search for k-variable subsets of a p-variable (p>k) data set that are optimal under some criterion. Search algorithms include a full search algorithm "leaps", based on Furnival and Wilson's leaps and bounds algorithm, and three random search algorithms: a genetic algorithm ("genetic"), a simulated annealing algorithm ("anneal") and a modified local search algorithm ("improve"). Previous versions of subselect had three criteria for optimal...

Version 0.9-99 of package "subselect" is now on CRAN. The subselect package has functions that search for k-variable subsets of a p-variable (p>k) data set that are optimal under some criterion. Search algorithms include a full search algorithm "leaps", based on Furnival and Wilson's leaps and bounds algorithm, and three random search algorithms: a genetic algorithm ("genetic"), a simulated annealing algorithm ("anneal") and a modified local search algorithm ("improve"). Previous versions of subselect had three criteria for optimal...

...hich are optimal under various criteria. As of version 0.7 a new function 'leaps' has been added. 'Leaps' performs a branch and bound search for the best variable subsets, according to a specified criterion. 'Leaps' implements Duarte Silva's adaptation (Reference 3) of Furnival and Wilson's Leaps and Bounds Algorithm for variable selection in Regression Analysis. It is viable in identifying optimal subsets for data sets with a moderate number (up to about 30-35) of variables, and very fast for small data sets (up to about 20-25 variables). In package subselect, the q...

...hich are optimal under various criteria. As of version 0.7 a new function 'leaps' has been added. 'Leaps' performs a branch and bound search for the best variable subsets, according to a specified criterion. 'Leaps' implements Duarte Silva's adaptation (Reference 3) of Furnival and Wilson's Leaps and Bounds Algorithm for variable selection in Regression Analysis. It is viable in identifying optimal subsets for data sets with a moderate number (up to about 30-35) of variables, and very fast for small data sets (up to about 20-25 variables). In package subselect, the q...