> Dear R users, > I am currently attempting to fit logistic regression models in R, where > the slopes should be restricted to positive values. Although I am aware >> I guess non-negative, as in the subject line, so there actually is a solution.
Indeed, I meant non-negative, zero slopes are also possible parameter values for my case. > of the package nnls (which does the trick for linear regression models), > I did not find any solution for logistic regression. If there is any > package available for this purpose, I would be interested to know them. > Alternatively, I realize it is possible to optimize a specialized > likelihood function that does the trick. Although I know how to optimize > the log-likelihood of logistic regression models, I am not sure how to > implement non-negativity constraints for slope parameters without > messing up the Newton optimization. Therefore, I am also interested in > solutions for this problem. >> There is an example of this in the 'Optimization' chapter of MASS (the book, page 445 to be precise). You simply use an optimizer with box constraints: see ?optim and ?nlminb, for example. Thanks a lot, I managed to get it fully working by passing the constraints to L-BFGS-B. ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
