glmulti: An R Package for Easy Automated Model Selection with (Generalized) Linear Models
AbstractWe introduce glmulti, an R package for automated model selection and multi-model inference with glm and related functions. From a list of explanatory variables, the provided function glmulti builds all possible unique models involving these variables and, optionally, their pairwise interactions. Restrictions can be specified for candidate models, by excluding specific terms, enforcing marginality, or controlling model complexity. Models are fitted with standard R functions like glm. The n best models and their support (e.g., (Q)AIC, (Q)AICc, or BIC) are returned, allowing model selection and multi-model inference through standard R functions. The package is optimized for large candidate sets by avoiding memory limitation, facilitating parallelization and providing, in addition to exhaustive screening, a compiled genetic algorithm method. This article briefly presents the statistical framework and introduces the package, with applications to simulated and real data.
Download InfoIf you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
Bibliographic InfoArticle provided by American Statistical Association in its journal Journal of Statistical Software.
Volume (Year): 34 ()
Issue (Month): i12 ()
Contact details of provider:
Web page: http://www.jstatsoft.org/
You can help add them by filling out this form.
Blog mentionsAs found by EconAcademics.org, the blog aggregator for Economics research:reading list or among the top items on IDEAS.Access and download statistics
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Christopher F. Baum).
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If references are entirely missing, you can add them using this form.
If the full references list an item that is present in RePEc, but the system did not link to it, you can help with this form.
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your profile, as there may be some citations waiting for confirmation.
Please note that corrections may take a couple of weeks to filter through the various RePEc services.