MARSS package uploaded to CRAN

The official release of 1.0 has been uploaded to CRAN (Here's the link to the CRAN page). This is an R package to fit unconstrained and constrained multivariate autoregressive state-space models via maximum-likelihood (EM algorithm). It was developed by Eli Holmes, Eric Ward and Kellie Wills. It is fully documented with a user guide/manual: Analysis of multivariate time-series using the MARSS package, by E.E. Holmes and E.J. Ward. MARSS has bootstrap AICb and CIs and simulation features. MARSS 1.0 doesn't allow you to estimate the B matrix. MARSS 2.0 will allow that, and MARSS 3.0 will provide Bayesian fitting. If you are looking for the derivation of update equations for the Kalman-EM algorithm, take a look at Derivation of the EM algorithm for constrained and unconstrained multivariate autoregressive state-space (MARSS) models.