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Projects for multivariate state space model:

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  • MARSS Dev Site

    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 state-space (MARSS) models with Gaussian errors to multivariate time series data.  A MARSS model is:

    x(t) = B(t) x(t-1) + 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 lag-one covariance smoother using an augmented state-space model that you can then run through the smoother to get the lag-one 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 pos-def 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 structure---however 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:

1-1 of 1 shown   (1 visible only to project members).    

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