Integral Projection Model

R script files for the general Integral Projection Model (S.P. Ellner and M. Rees 2006, American Naturalist ). There is a readme.pdf file, but most explanation is in the form of comments within the script files.  

Matlab and R/Splus code for a basic Integral Projection Model with one individual-state variable (Easterling, Ellner, and Dixon 2000). Zip file including script files and a manual (MS Word and PostScript). Still functional, but the newer scripts (above) use better methods and will be easier to adapt for your own purposes (we hope!)

    

LENNS and nnreg: Lyapunov exponents and neural network time series models

The LENNS package ('Lyapunov Exponents for Noisy Nonlinear Systems') was originally standalone f77, but then it got merged into the FUNFITS package for S-plus. FUNFITS is still available (see below) but is now 'frozen' meaning that it probably won't work with a current version of S-plus. Most of its functionality has been incorporated into the fields package for R that can be gotten from CRAN (www.cran.r-project.org). The rest -- neural networks, global and local Lyapunov exponents -- is here.

Lenns.zip: LENNS and nnreg for R/Windows. This is not really a package, and it only works under Windows. Create a folder c:\lenns and then extract the contents of Lenns.zip into the lenns folder using folder names. This will create a folder tree c:\lenns\chtml,c:\lenns\exec, etc. It is not in shape to be installed from within R (that used to work, but not since the rules changed with R 2.0) -- you will need to source() code from within an R session. The file readme.lenns tells you what to do. There is a set of html help pages that can be accessed from lenns/html/00Index.html. Sorry, this is the best I can do right now. If you have trouble getting it to run, let me know. If you unzip it into c:\lenns, it should work "out of the box" after you source lenns.R.

The rest of the FUNFITS package (i.e., everything but neural nets) is supplanted by the fields library for R (available at CRAN . A "frozen" version of FUNFITS for S-plus (UNIX only) is available at Statlib. For a S-plus Windows version, contact Doug Nychka (nychka.ATSIGN.gcd.ucar.edu). A port to R is apparently available for Redhat Linux, but I have no experience with it.

    

Gradfit: Gradient matching and monotone regression splines

This is the set of R functions for nonparametric (regression spline) fitting of delay differential equations associated with S.P. Ellner, Y. Seifu and R.H. Smith (2002) "Fitting population dynamic models to time series data by gradient matching" (Ecology 83: 22562270). It includes functions for functions for smoothing a time series to estimate its gradient, and support routines for fitting monotone spline regression and bivariate additive spline regression models with sign constraints, with smoothing parameter selection by GCV.
GradFuncs.zip - Zip archive of all files
Readme.txt - Readme file for the Zip archive
GradFuncs.R - R source code for the fitting functions. Requires the MASS and quadprog libraries and version 1.1 or higher of R
TestGradFuncs.R - Examples of using the main fitting functions, extensively commented. Requires the mgcv library.
GradFuncs.doc - Documentation in MS Word for Windows format
GradFuncs.pdf - Documentation in PDF format
Nichadults.txt - Data file used by the examples: every-other-day count of adult numbers in series "I" from Nicholson (1957). The example code assumes that this file is sitting in C:\GradFuncs; if you put it anywhere else you need to edit the example code appropriately
The examples file TestGradFuncs.R illustrates how the functions are used, including an example of a SIMEX bias-correction for measurement errors. Please note that this is not a library; the script file GradFuncs.R must be source'd to make the functions available in the current session. There is also no online help provided. Adapting the functions to work in Splus should be fairly easy. The main R-specific feature is the use of optim() with method = "Nelder-Mead" to optimize the smoothing parameters in additive models; a call to nlmin() could be substituted. Also, one commented-out line near the top of GradFuncs.R needs to uncommented so that the Splus solve.matrix() is called in place of solve(). Several of the examples use R-specific plotting parameters.     

Other Software

STAGECOACH (Cochran and Ellner 1992). As a Zip file. Contains f77 source code (we wrote this in 1990, and back then C still looked like it might be the next Pascal) and a standalone executable that runs in a Windows command window. This code corresponds to the formulas in Cochran and Ellner (1992). Caswell's 2nd edition describes how to get the same results using Matlab rather than do-loops.

Simulation model of recirculating mariculture system (Ellner et al. 1996, Aquaculture) As a zip file.  

Simulation model of recirculating mariculture system (Ellner et al. 1996, Aquaculture) Documentation: pdf.  

Simulation model of recirculating mariculture system (Ellner et al. 1996, Aquaculture) Documentation: ppt.