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Computing Interests

My main computing interests are in agent based models and Bayesian hierarchical models. I program almost exclusively in R, although I do occasionally work with MatLab and Mathematica.

Code examples

Agent based models

Here is code for an agent based model of a three species metacommunity. The code has been written to run on a Linux node at the Vermont advanced computing center (VACC), but I have visualization code for the output and code that can visualize model runs. Please contact me if you are interested. You can see the model code here

The above model is a fancier version of an initial mockup I did in NetLogo, you can see my code here

I am also interested in other computational methods as they apply to ecology such as evolutionary computation and cellular automata models. Here is a simple GA written in R to solve the simple one max problem. Here is my solution

Bayesian computation

I do much of my Bayesian computation using WinBUGS, but I also hand code samplers when I need to. Here are two examples.

A home grown metropolis sampler MH_Norm: fort estimating the parameters for a normal distribution from a vector of random normal numbers and then an example with linear regression

Sample code from my hierarchical time series models, this is an example that runs on the VACC again for Mosquitoes

Bayesian Resources

A few blogs that I read regularly are those by Jim Albert, and Andrew Gelman.

I also have used the following books to help teach myself

Jim Clark's Models for Ecological Data

Jim Albert's Bayesian Computation in R

And a couple books by Andrew Gelman:

Data analysis using regression and multilevel/hierarchical models

Bayesian data analysis

Of course I also rely on my adviser Nick Gotelli's book A primer of Ecological Statistics