This package implements the simulations and data analysis examples for compressed and penalized linear regression as in (Homrighausen and McDonald, 2017). Essentially, the design matrix is premultiplied by a sparse matrix, reducing the number of available observations from n to q. However, the addition of a ridge penalty results in estimates of the true coefficient vector with lower mean-squared error, even relative to ridge regression (in some cases). The result is improved computation and better statistical accuracy.
Package details |
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Maintainer | |
License | GPL |
Version | 0.2.0 |
URL | http://github.com/dajmcdon/cplr |
Package repository | View on GitHub |
Installation |
Install the latest version of this package by entering the following in R:
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