Computing and Statistics

Improve Performance

Programing and Data Analysis

Data Management

Generalized Linear Mixed Models

R Packages:

  • lme4
  • glmmPQL {MASS}
  • glmmML
  • glmmADMB {ADMB} (I have trouble installing properly – haven’t got it to run)
  • MCMCglmm
  • unmarked (calculate abundance, occupancy, and detection from repeated survey data)
  • RStan
  • nlme
  • geepack
  • QICpack
  • AICcmodavg
  • ggplot2
  • lattice
  • parallel
  • rjags
  • R2jags
  • R2WinBUGS
  • MASS
  • IPMpack
  • gamm4
  • stargazer – The stargazer command produces LaTeX code for well-formatted tables that hold regression analysis results from several models side-by-side, as well as summary statistics. More info here
  • boot
  • car – Companion to Applied Regression book by John Fox. Easiest way to run ANOVAs in R.
  • knitr – fantastic package for creating markdown files in R. Great with RStudio

Model Selection and Overfitting:
Overfitting (John White Blog)

Useful R Scripts

Computing Resources

  • Stack Overflow – Great forum for computer coding (any language including R)
  • Cross Validated – Stack Exchange forum for statistics
  • Parallel Processing to speed up complex models
  • Dropbox I love Dropbox! I haven’t used my USB flash drive in 2 years since starting with it. I had my dissertation and data backed up via Dropbox and could access it on any computer. 2 GB free. You can also share folders with friends that have Dropbox. I share research files with collaborators. Much better than trying to email files back and forth.

Recommendations for Analysis and Data Presentation
Avoid Dynamite Plots: From Bolker, Resource with some R code, Vanderbilt Wiki (definitely view linked poster)

Other Resources

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