This library performs an exhaustive search for the best subsets of a given
set of potential regressors, using a branch-and-bound algorithm, and also 
performs searches using a number of less time-consuming techniques. It is
designed to replace the "leaps()" command in S.  It is based on FORTRAN77
code by Alan Miller of CSIRO Division of Mathematics & Statistics
(<Alan.Miller@vic.cmis.csiro.au>) which is described in more detail in his
book "Subset Selection in Regression".  Parts of the code have been
published in the Applied Statistics algorithms series. 

There are several minor but useful improvements over S implementation. 
Firstly, there is no hard-coded limit to the number of variables.
Secondly, it is possible to restrict the search to subsets of at most a
specified size, potentially giving a large saving in time. Thirdly, it is
not necessary that the matrix of possible predictors be of full rank. This
is particularly useful when there are more predictors than cases and the
best "small"  model is wanted. 


Thomas Lumley
Biostatistics, University of Washington, Seattle
tlumley@u.washington.edu



