Twotorials by anthony damico. Ecological Models and Data in R. This is the web site for a book published by Princeton University Press (ISBN 0691125228).
It is available from Princeton University Press and Amazon.com. Data and scripts for labs: Other data and scripts: Most of the data for the book are available in the emdbook package on CRAN. If you would like the goby data (in the emdbookx package), please contact me (bolker at ufl.edu). Most of the R code for doing things in the book is now in the two packages bbmle (also available in a development version) and emdbook, both available from R archive (CRAN) or via install.packages from inside R. Other miscellaneous R code: pdfhtmlxmlRnwR Warning: everything below here may be somewhat out of date ...If you want to see the existing notes for the course, start here.
Old PDFs An old draft: 3 August 2007 (PDF, 6 MB). Individual chapters Last update: 27 December 2006. Common Concepts in Statistics [M.Tevfik DORAK] Genetics Population Genetics Genetic Epidemiology Bias & Confounding Evolution HLA MHC Homepage M.Tevfik Dorak, MD, PhD Please use this address next time: See also Common Terms in Mathematics; Statistical Analysis in HLA & Disease Association Studies; Epidemiology (incl.
![Common Concepts in Statistics [M.Tevfik DORAK]](http://cdn.pearltrees.com/s/pic/th/common-concepts-statistics-48092260)
Genetic Epidemiology Glossary) An R Introduction to Statistics. Statistics with R. Warning Here are the notes I took while discovering and using the statistical environment R.
However, I do not claim any competence in the domains I tackle: I hope you will find those notes useful, but keep you eyes open -- errors and bad advice are still lurking in those pages... Should you want it, I have prepared a quick-and-dirty PDF version of this document. The old, French version is still available, in HTML or as a single file. You may also want all the code in this document. 1. This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 2.5 License.
Software - Miquel De Cáceres Ainsa. Indicspecies R package Indicator species are species that are used as ecological indicators of community or habitat types, environmental conditions, or environmental changes.
In order to determine indicator species, the characteristic to be predicted is represented in the form of a classification of the sites, which is compared to the patterns of distribution of the species found in that set of sites. 'Indicspecies' is an R package that contains a set of functions to assess the strength of relationship between species and a classification of sites. As such, it includes the well-known IndVal method (Dufrêne & Legendre 1997) and extends it by allowing the user to study combinations of site groups (De Cáceres et al. 2010). Apart from the IndVal index, the package allows computing many other indices suitable for this kind of associations (De Cáceres & Legendre 2009), such as the phi coefficient of association. Knitr: Elegant, flexible and fast dynamic report generation with R. Overview The knitr package was designed to be a transparent engine for dynamic report generation with R, solve some long-standing problems in Sweave, and combine features in other add-on packages into one package (knitr ≈ Sweave + cacheSweave + pgfSweave + weaver + animation::saveLatex + R2HTML::RweaveHTML + highlight::HighlightWeaveLatex + 0.2 * brew + 0.1 * SweaveListingUtils + more).
This package is developed on GitHub; for installation instructions and FAQ’s, see README. This website serves as the full documentation of knitr, and you can find the main manual, the graphics manual and other demos / examples here. For a more organized reference, see the knitr book. NumericalEcology.com.
Vanderbilt Biostatistics Wiki. Rtips. Revival 2012! Paul E.
Johnson <pauljohn @ ku.edu> The original Rtips started in 1999. It became difficult to update because of limitations in the software with which it was created. Now I know more about R, and have decided to wade in again. In January, 2012, I took the FaqManager HTML output and converted it to LaTeX with the excellent open source program pandoc, and from there I’ve been editing and updating it in LyX. You are reading the New Thing! The first chore is to cut out the old useless stuff that was no good to start with, correct mistakes in translation (the quotation mark translations are particularly dangerous, but also there is trouble with ~, $, and -. (I thought it was cute to call this “StatsRus” but the Toystore’s lawyer called and, well, you know…) If you need a tip sheet for R, here it is.
This is not a substitute for R documentation, just a list of things I had trouble remembering when switching from SAS to R. Heed the words of Brian D. 1.1 Bring raw numbers into R (05/22/2012) Step 1. Abcd'R - astuces et Scripts R. Statconn.