Description: Abstract There a number of interesting variable selection methods available beside the regular forward selection and stepwise selection methods. Such approaches include LASSO (Least Absolute Shrinkage and Selection Operator), least angle regression (LARS) and elastic net (LARS-EN) regression. There also exists a method for calculating principal components with sparse loadings. This software package contains Matlab implementations of these functions. The standard implementations of these functions are available as add-on packages in S-Plus and R.
Keywords LASSO, LARS, SPCA, Matlab, Elastic Net, Sparse, Sparsity, Variable selection
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LASSO&LARS& SPCA\center.m
................\crossvalidate.m
................\cvplot.m
................\diabetes.mat
................\lars.m
................\larsen.m
................\larsen_test.m
................\lars_test.m
................\lars_test2.m
................\normalize.m
................\readme.txt
................\spca.m
................\spca_test.m
................\standardize.m
LASSO&LARS& SPCA
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