Projects for multivariate state space model: 
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MARSS Dev Site
by e2holmes, last updated 8/30/12, sharing set to public
This is the DEVELOPMENT site for the MARSS. For the current MARSS release go to CRAN or download straight from the R GUI using "Install Packages" menu.
MARSS fits mulitvariate autoregressive statespace (MARSS) models with Gaussian errors to multivariate time series data. A MARSS model is:
x(t) = B(t) x(t1) + u(t) + C(t)c(t) + v(t), v(t)~MVN(0,Q)
y(t) = Z(t) x(t) + a(t) + D(t)d(t) + w(t), w(t)~MVN(0,R)
Project news (Feb 26, 2013): MARSS 3.4 uploaded to CRAN. I fixed MARSSkfas to work with the new KFAS package in order to use the Koopman/Durbin filter/smoother algorithms. I also coded up a lagone covariance smoother using an augmented statespace model that you can then run through the smoother to get the lagone covariances. I added a coef() and residuals() method to improve output.
Developers: Eli Holmes, Eric Ward, Mark Scheuerell and Kellie Wills
Current known issues:
 When variance is "unconstrained", the covariances can be set to 0 in the degen.test() and this leads to not posdef matrix and error. Need to block setting to 0 when this happens, or block covariances set to zero? Currently, deal with this by setting allow.degen=FALSE when covariances are estimated.
 demean.states=TRUE is causing the EM algorithm to give drops in logLik. This is not really a bug but perhaps a property of demean.states. Removed the demean.states option in vrs 3.3.
MARSS 4.0 in progress:
 4.0 involves a substantial change in the model object structurehowever the user should not notice the difference. The change allows the developers to more easily code up new model structures.
 Progress continues on writing functions for standard output, e.g. predict function added.
 Integration with LateX begun so that output can be sent to a tex or pdf file instead of just the console.
Projects for multivariate state space model: 
11 of
1
shown (1 visible only to project members).

