This package uses the marginal relationship between predictor variables and a response to identify a small subset of measurements which appear relevant for prediction, produce a lowdimensional linear embedding based on this small subset, and amplify this embedding with information from the remaining measurements. The goal is to perform principle components regression (PCR), but in high dimensional settings where the number of measurements exceeds the number of observations. The technique employed uses some approximation methods to increase statistical and computational efficiency.
Package details 


Maintainer  
License  GPL 
Version  0.1.0 
URL  http://github.com/dajmcdon/aimer 
Package repository  View on GitHub 
Installation 
Install the latest version of this package by entering the following in R:

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