Introducing Influence.ME: Tools for detecting influential data in mixed models

April 29, 2009
By

(This article was first published on Curving Normality » R-Project, and kindly contributed to R-bloggers)

I’m highly excited to announce that influence.ME is now available. Influence.ME is a new software package for R, providing statistical tools for detecting influential data in mixed models. It has been developed by Rense Nieuwenhuis, Ben Pelzer, and Manfred te Grotenhuis. The basic rationale behind identifying influential data is that ...

To leave a comment for the author, please follow the link and comment on his blog: Curving Normality » R-Project.
R-bloggers.com offers daily e-mail updates about R news and tutorials on topics such as: visualization (ggplot2, Boxplots, maps, animation), programming (RStudio, Sweave, LaTeX, SQL, Eclipse, git, hadoop, Web Scraping) statistics (regression, PCA, time series,ecdf, trading) and more...

If you got this far, why not subscribe for updates from the site? Choose your flavor: e-mail, twitter, RSS, or facebook...

Tags: , , , ,

Comments are closed.

Top 7 articles of the week

  1. Quandl Package - 5,000,000 free datasets at the tip of your fingers!
  2. Google Analytics + R = FUN!
  3. How R Grows
  4. Writing from R to Excel with xlsx
  5. FasteR! HigheR! StongeR! - A Guide to Speeding Up R Code for Busy People
  6. Select operations on R data frames
  7. TV shows rated by episode as a Shiny App

Sponsors

Mango solutions
mango-solutions.com
Zero Inflated Models and Generalized Linear Mixed Models with R
Quantide: statistical consulting and training
RStudio homepage
RStudio: a free and open source IDE for R
REvolution analytics
HMS Analytical Software GmbH
http://www.eoda.de
Zero Inflated Models and Generalized Linear Mixed Models with R Zero Inflated Models and Generalized Linear Mixed Models with R. Zuur, Saveliev, Ieno (2012).