This dataset is a matrix of 200 rows and 28 colums. The columns can be
grouped as three blocs of 9 (for each method compared:
RIDGE, Elastic net [
ELNET], Stepwise variable selection
CLERE, CLERE sparse [
CLERE_s], Spike and Slab
AVG method and Pairwise Absolute Clustering and Sparsity
PACS]). Prediction errors (MSE), number of estimated parameters and
time (seconds) to fit the data are compared.The 1st 9 (1:9) contain
prediction error obtained by 5-fold cross validation using 10 random
permutation of the covariate matrix. The 2nd 9 columns (10:18) contain the
number of parameters estimated for each method. The 3rd 9 columns are times
in seconds measured for fitting each methods. The 28 column is the seed
utilized for generating random numbers in these analyses. Each row
corresponds to a simulated dataset on which all 9 methods were fitted. For
more details, please refer to the package vignette. The R script used to
create this dataset is clere/inst/doc/SimulatedDataExample.R.
A 200 x 28 matrix.
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