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 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.