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Please download the current release of MARSS from CRAN. The current User Guide can be found there also.

A MARSS model is a multivariate auto-regressive time-series model of the form:

x(t) = B x(t-1) + u + v(t), v(t)~MVN(0,Q)

y(t) = Z x(t) + a + w(t), w(t)~MVN(0,R)

where all elements of these equations are matrices as this is a multivariate auto-regressive model.

What you need to use this code: MARSS is an R package, thus you need to install R from CRAN in order to use the package  Once you have R installed, then install the MARSS package using the standard R package instructions (if you are using an R GUI, then you use the "Install Packages" menu.)  If you have never done this, see the instructions on CRAN.

About this code: This code is used to estimate maximum likelihood parameters for multivariate state space time series models via an EM algorithm using the Kalman filter+smoother. We have a number of online workshops on multivariate state-space models available with case studies and examples for estimating trends, evaluating population structure, estimating interactions, and analyzing movement data: WORKSHOPS  Our EM algorithm is similar to that in Shumway and Stoffer (1982) but actually was inspired by Ghahramani and Hinton (1996). Most other software uses the BFGS algorithm (a quasi-Newton method) for maximization, which often works great but for some models needs a bit of fiddling to get it to work (not throw numerical errors).  Some researchers will use the EM algorithm to "get close" and then polish off with the BFGS algorithm.  MARSS includes functions for bootstrapping (parametric and innovations), model selection (AIC, AICc, and bootstrap bias-corrected AICb), confidence intervals (approximate via Hessian, parametric bootstrap, and innovations bootstrap), parameter bias estimation (via bootstrapping), simulation, and initial condition searching.  MARSS was developed by Eli Holmes, Eric Ward, and Kellie Wills.

See what is coming in the next MARSS version: This is our development site MARSS development site

Learning how to use the code: The user manual gives detailed examples. Scripts and data for all the case studies are included in the package. Our online workshops at EE Holmes' website include pdfs of our lectures.

See our personal websites for group news on papers coming out of this work: EE Holmes website, Eric Ward website, Brice Semmens website, and Mark Scheuerell website.  (download stats from CRAN)



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