Wednesday, August 1, 2012

Time-series analysis course winter 2012

Fish 50X: Applied Time Series Analysis in Fisheries and Environmental Sciences
Winter 2012
Fisheries Dept, University of Washington

Instructors: Eric Ward, Eli Holmes, Mark Scheuerell
email: eli.holmes@noaa.gov, mark.scheuerell@noaa.gov, eric.ward@noaa.gov

Reviews current applications of univariate and multivariate time series models for biological and environmental data, emphasizing the estimation, inference, and forecasting aspects of time-series models. Explores effects of covariates and anthropogenic drivers for species that are exploited and/or of conservation concern. Recommended: FISH 552 or prior experience with R (e.g. FISH 560), QSCI 482 or basic statistics, and at least 1 course in population dynamics (FISH 454 or 458).

R Journal article on the MARSS package

Holmes, E. E., Ward, E. J. and K. Wills. 2012. MARSS: Multivariate autoregressive state-space models for analyzing time-series data. R Journal 4: 11-19.  http://journal.r-project.org/archive/2012-1/RJournal_2012-1_Holmes~et~al.pdf

MARSS 3.1 released on CRAN

MARSS 3.1 is now up on CRAN.  This allows for time-varying constraints and covariates.  See the updated User Guide (on CRAN).  The major changes are internal and allow for us easily write customized functions for different MARSS forms (like AR-p processes and DFA models).   3.1 is considerably slower than 2.x, however this should be fixed in 3.2 or 3.3 when the Kalman filter in the KFAS package can be hooked back up to MARSS (temporarily disabled). http://cran.r-project.org/web/packages/MARSS