Constrained Optimization on Linear Function

Performs least squares constrained optimization on a linear objective function. It contains a number of algorithms to choose from and offers a formula syntax similar to lm().


A package to perform a least squares constrained optimization on a linear objective function. It provides a very easy way to run a constrained linear regression using the lm formula syntax that most R users are familiar with.

Then to install colf run the following on your console:

devtools::install_github('lyzander/colf')

By typing on your console:

library(colf)
colf_nls(mpg ~ ., mtcars, upper = rep(2, 11), lower = rep(-0.5, 11))

you can see a first example of how to run a constrained optimization on a linear objective function!

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Reference manual

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install.packages("colf")

0.1.2 by Theo Boutaris, 6 months ago


https://github.com/LyzandeR/colf


Report a bug at https://github.com/LyzandeR/colf/issues


Browse source code at https://github.com/cran/colf


Authors: Theo Boutaris [aut, cre, cph]


Documentation:   PDF Manual  


MIT + file LICENSE license


Depends on nlmrt, stats

Suggests testthat, knitr, rmarkdown


See at CRAN