Facilitates data simulation from a random regression model where the data properties can be controlled by a few input parameters. The data simulation is based on the concept of relevant latent components and relevant predictors, and was developed for the purpose of testing methods for variable selection for prediction. Included are also functions for designing computer experiments in order to investigate the effects of the data properties on the performance of the tested methods. The design is constructed using the Multilevel Binary Replacement (MBR) design approach which makes it possible to set up fractional designs for multifactor problems with potentially many levels for each factor.
Package details 


Author  Solve Sb 
Date of publication  20141129 07:59:54 
Maintainer  Solve Sb <[email protected]> 
License  GPL2 
Version  1.01 
Package repository  View on CRAN 
Installation 
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