CV

Research

Lab Code

Links

Beyond Science

Kalman-EM in R

Kalman-EM algorithms for fitting MSSMs This is an R toolbox. Written by Eric Ward and Eli Holmes. The case-studies on the code website are the defacto help files and documentation. An on-line workshop on state-space modeling using the Kalman-EM R toolbox is available here: State-space modeling workshop. The current public 'release' is from Aug 2008, and we are in active code development. We have a stable new version with many new features (like bootstrap AICb and CIs), but we need to update our documentation before releasing. Contact Eli or Eric if you want the current code.

LAMBDA

LAMBDA: Long-term Assemblage MAR(1)-Based Data Analysis LAMBDA is a MatLab toolkit designed to do MAR-1 based data analysis on long-term datasets (i.e., time series). LAMBDA is designed to allow the user to step through the entire modeling process, from transforming the data, to model selection, to fitting the MAR-1 regression model and obtaining output parameters with bootstrapped CIs (see Ives et al. 2003, Ecological Monographs 73:301-330). Developed by Steven Viscido and Eli Holmes. An on-line workshop on MAR-1 modeling of community data using LAMBDA is available here: MAR workshop

MixSIR

MixSIR download and manual page MixSIR is a Bayesian isotope mixing model that incorporates uncertainty in the estimates of mix and source isotope values. The model also provides the opportunity to incorporate prior information for the proportional contribution of each source to the mix. Developed by Brice Semmens and Jon Moore.

BEAST

beast website BEAST provides a flexible modelling tool for theoretical biologists to evaluate population models in a Bayesian framework. A variety of models are supported: single stage / age models, stage-structured population models, and age-structured population models. All models support variable change points (broken stick models), time lags, and error may be incorporated in the form of either observation error or process error. A wide range of symmetric and asymmetric likelihoods are supported, and any one of the ~ 25 prior distributions may be placed on any parameter in the model. BEAST also allows the user to do MCMC parameter estimation, population projections, and to conduct formal Bayesian decision analyses. Developed by Eric Ward.

Searchable code libraries

As part of our Iugo-Cafe project, we have developed searchable ecological code repositories:

Our code on FishBox and EcologyBox

Much of the work by Brice Semmens, Eric Ward, Steve Viscido and myself (Eli Holmes) has been focused on fitting multivariate autoregressive models (MARMs) and multivariate state-space models (MSSMs). We are developing code/algorithms for maximum-likelihood and Bayesian approaches using Kalman filter and EM, data-cloning, and Gibbs-sampler algorithms. You can use the code (with attribution), but contact us because this is research in progress and we may have bugs/problems/whatever to share. Also we like to collaborate with folks on an analyses of interesting ecological data (first.last@noaa.gov), so you should feel free to drop us a line.

The following is older code that I haven't worked on since 2005-2007. This include the "slope" method (Holmes 2001) approach which I don't use much for research much now (although I did use it in Holmes et al. 2007). But I do use it for applications. It is a bit ad hoc, but it consistently performs better than any other approach I know of on very corrupted data. And Steve Ellner and I showed recently (in Ecol Letters) that the slope methods produced estimates that are very close to the theoretical minimum uncertainty.