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). This is mostly
for archival purposes; the scripts are not guaranteed to work
and the methods are outdated.

The
LENNS package ('Lyapunov Exponents for Noisy Nonlinear Systems') was originally
standalone f77 but then was merged into the FUNFITS package for S-plus. FUNFITS
is defunct but most of its functionality has been moved into the **fields** package for R, which you can get
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 cannot be installed from within R (that used to work, but not since the rules changed with R 2.0). Instead, you need to source() the lenns.R scripts from within a running R session. The file readme.lenns tells you what to do, and help can be accessed by opening lenns/html/00Index.html with a browsers. If you have trouble getting it to run, let me know.

The rest of the FUNFITS package (i.e., everything but neural nets) is
supplanted by the **fields** package for
R (available at CRAN .

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:
2256–2270). 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 -Rsource code for the fitting functions. Requires theMASSandquadproglibraries and version 1.1 or higher ofR

TestGradFuncs.R - Examples of using the main fitting functions, extensively commented. Requires themgcvlibrary.

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.

STAGECOACH (Cochran and Ellner 1992). As a Zip file. Contains f77 source code (we wrote this in 1990, when 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 (2001) describes how to get the same results using Matlab rather than do-loops. STAGECOACH defines lifespan as ‘maximum lifespan consistent with how often an individual was censused’, so an annual has a lifespan of 2 and a generation time of 2. In retrospect that was not the best possible idea, but it is easy to fix by subtracting 1 from the affected life history attributes.

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