Applied Time Series Analysis

Courses, eBooks, R Packages, and Publications

section icon

Applied Time-Series Analysis for Fisheries and Environmental Data

Course Website
Lectures pdfs, lecture video recordings, course handouts and exercises.
Online book based on the course and computer labs.

Fish Forecast

Course Website
Use R to model and forecast catch time series using a variety of standard forecasting models.
Online book based on the course and computer labs.
section icon

R Packages available on CRAN and GitHub

Multivariate Autoregressive State-Space Modeling with R. Includes a book: Analysis of multivariate time series using the MARSS package.
Applied time series analysis in R with Stan. Fast fitting of Bayesian multivariate time-series models. See our ATSA book for applications.
Time-varying vector autoregressive state-space modeling of community interactions. Fit time-varying B matrices in a Bayesian framework.
section icon

Our publications related to multivariate time-series analysis

This is a selection of NWFSC papers using MARSS modeling. See our individual websites for our publications on other topics.

  • Nogueira, A., N. Tolimieri, and D. González-Troncoso. 2018. Using multivariate state-space models to examine commercial stocks of redfish (Sebastes spp.) on the Flemish Cap. Canadian Journal of Fisheries and Aquatic Sciences. Published on the web 17 April 2018,

  • Ward, E. J., K. Oken, K. A. Rose, S. Sable, K. Watkins, E. E. Holmes, and M. D. Scheuerell. 2018. Applying spatiotemporal models to monitoring data to quantify fish responses to the Deepwater Horizon oil spill in the Gulf of Mexico. Environmental Monitoring and Assessment 190:530.

  • Ward, E.J., M. Adkison, J. Couture, S. C. Dressel, M. A. Litzow, S. Moffitt, T. Hoem Neher, J. Trochta, and R. Brenner. 2017. Evaluating signals of oil spill impacts, climate, and species interactions in Pacific herring and Pacific salmon populations in Prince William Sound and Copper River, Alaska. PLOS ONE, 12(3): e0172898.

  • Holmes, E.E., M. D. Scheuerell, and E. J. Ward. 2017. Applied Time Series Analysis for Fisheries and Environmental Sciences. Online text for our course at University of Washington. Online

  • Tolimieri, N., E. E. Holmes, G. D. Williams, R. Pacunski, and D. Lowry. 2017. Population assessment using multivariate time-series analysis: A case study of rockfishes in Puget Sound. Ecology and Evolution 7(8): 2045-7758. PDF

  • Goertler, P. A. L., M. D. Scheuerell, C. A. Simenstad, D. L. Bottom. 2016. Estimating common growth patterns in juvenile Chinook salmon (Oncorhynchus tshawytscha) from diverse genetic stocks and a large spatial extent. PLoS ONE 11:e0162121 PDF

  • Ohlberger J., M. D. Scheuerell, and D. E. Schindler. 2016. Population coherence and environmental impacts across spatial scales: a case study of Chinook salmon. Ecosphere 7:e01333 PDF

  • Jorgensen J. C., E. J. Ward, M. D. Scheuerell, and R. W. Zabel. 2016. Assessing spatial covariance among time series of abundance. Ecology and Evolution 6:2472–2485 PDF

  • Scheuerell M. D., E. R. Buhle, B. X. Semmens, M. J. Ford, T. Cooney, R. W. Carmichael. 2015. Analyzing large-scale conservation interventions with Bayesian hierarchical models: A case study of supplementing threatened Pacific salmon. Ecology and Evolution 5:2115–2125 PDF

  • Ford, M. J., K. Barnas, T. Cooney, L. G. Crozier, M. Diaz, J. J. Hard, E. E. Holmes, D. M. Holzer, R. G. Kope, P. W. Lawson, M. Liermann, J. M. Myers, M. Rowse, D. J. Teel, D. M. Van Doornik, T. C. Wainwright, L. A. Weitkamp, M. Williams. 2015. Status Review Update for Pacific Salmon and Steelhead Listed under the Endangered Species Act: Pacific Northwest. National Marine Fisheries Service, Northwest Fisheries Science Center. PDF

  • Ruhi, A., E. E. Holmes, J. N. Rinne, and J. L. Sabo. 2015. Anomalous droughts, not invasion, decrease persistence of native fishes in a desert river. Global Change Biology 21:1482-1496. html PDF

  • Lisi P. J., D. E. Schindler, T. J. Cline, M. D. Scheuerell, P. B. Walsh. 2015. Topography and snowmelt control stream thermal sensitivity to air temperature. Geophysical Research Letters 42:3380-3388 PDF

  • Griffiths J. R, D. E. Schindler, J. B. Armstrong, M. D. Scheuerell, D. C. Whited, R. A. Clarke, R. Hilborn, C. A. Holt, S. T. Lindley, J. A. Stanford, and E. C. Volk. 2014. Performance of salmon fishery portfolios across western North America. Journal of Applied Ecology 51:1554–1563

  • Francis, T. B., E. M. Wolkovich, M. D. Scheuerell, S. L. Katz, E. E. Holmes, and S. E. Hampton. 2014. Shifting Regimes and Changing Interactions in the Lake Washington, USA, Plankton Community from 1962-1994. PlosOne e110363. PDF

  • Holmes, E. E. 2014. Computation of standardized residuals for (MARSS) models. Technical Report. arXiv:1411.0045 PDF

  • Ward, E. J., E. E. Holmes, J. T. Thorson, and B. Collen. 2014. Complexity is costly: a meta-analysis of parametric and non-parametric methods for short-term population forecasting. Oikos, 123(6): 652-661. PDF

  • Hampton, S. E., E. E. Holmes, D. E. Pendleton, L. P. Scheef, M. D. Scheuerell, and E. J. Ward. 2013. Quantifying effects of abiotic and biotic drivers on community dynamics with multivariate autoregressive (MAR) models. Ecology 94(12): 2663-2669. PDF

  • Holmes, E. E. 2013. Derivation of the EM algorithm for constrained and unconstrained multivariate autoregressive state-space (MARSS) models. Technical Report. arXiv:1302.3919 PDF

  • Holmes, E. E., E. J. Ward, and K. Wills. 2012. MARSS: multivariate autoregressive state-space models for analyzing time series data. R Journal 4(1): 11-19. PDF

  • Scheef, L. P., D. E. Pendleton, S. E. Hampton, S. L. Katz, E. E. Holmes, M. D. Scheuerell, and D.G. Johns. 2012. Assessing marine plankton community structure from long-term monitoring data with multivariate autoregressive (MAR) models: a comparison of fixed station vs. spatially distributed sampling data. Limnology & Oceanography: Methods 10: 54-64. PDF

  • Francis T. B., M. D. Scheuerell, R. Brodeur, P. S. Levin, J. J. Ruzicka, N. Tolimieri, and W. T. Peterson. 2012. Climate shifts the interaction web of a marine plankton community. Global Change Biology 18:2498–2508

  • Crozier L. G., M. D. Scheuerell, and R. W. Zabel. 2011. Using time series analysis to characterize evolutionary and plastic responses to environmental change: a case study of a shift toward earlier migration date in sockeye salmon. The American Naturalist 178:755-773

  • Pattengill-Semmens, C. V., Semmens, B. X., E. E. Holmes, E. J. Ward, and B. I. Ruttenberg. 2011. Integrating time-series of community monitoring data. Proceedings of the Gulf and Caribbean Fisheries Institute 63: 214-216. PDF

  • Drake, J., E. A. Berntson, J. M. Cope, R. G. Gustafson, E. E. Holmes, P. S. Levin, N. Tolimieri, R. S. Waples, S. Sogard, and G. D. Williams. 2010. Status review of five rockfish species in Puget Sound, Washington: Bocaccio (Sebastes paucispinis), canary rockfish (S. pinniger), yelloweye rockfish (S. ruberrimus), greenstriped rockfish (S. elongatus), and redstripe rockfish (S. proriger). U.S. Dept. of Commerce, NOAA Tech. Memo., NMFS-NWFSC-108. PDF

  • Ward, E. J., H. Chirrakal, M. Gonzalez-Suarez, D. Aurioles-Gamboa, E. E. Holmes, and L. Gerber. 2010. Inferring spatial structure from time-series data: using multivariate state-space models to detect metapopulation structure of California sea lions in the Gulf of California, Mexico. Journal of Applied Ecology 47: 47-56. PDF

  • Holmes, E. E. and E. J. Ward. 2010. Analysis of multivariate time series using the MARSS package PDF. User Guide for the MARSS R package

  • Viscido, S. V. and E. E. Holmes. 2010. Statistical modelling of communities and ecosystems using the LAMDA software tool. Environmental Modelling and Software 25(12): 1905-1908. PDF

  • Hampton S. E., M. D. Scheuerell, and D. E. Schindler. 2006. Coalescence in the Lake Washington story: interaction strengths in a planktonic food web. Limnology and Oceanography 51:2042-2051

section icon

Please see our individual websites for our contact information