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Projects found

Projects for multivariate autoregressive:

1-2 of 2 shown   (1 visible only to FishBox members).    
    
1  

  • Bayesian MAR(1) model

    This set of Matlab scripts conducts a first order MAR(1) model to estimate interactive effects, and covariate effects, on a time series of data from a community.

    It uses a Gibbs sampler to estimate parameters, and currently is set up with diffuse priors on all parameters for the model. It is pretty basic at this point, but it works.

    Note on the Gamma distribution:

    Going back and forth between Matlab/R/WinBUGS can be confusing, because of the different parameterizations of the gamma pdf. Here's the Matlab/BUGS forms and the R equivalents:

    Matlab: X ~ g(a,b) E[X] = ab

    R equivalent: X ~ g(shape=a,scale=b)

    BUGS: X ~ g(a,b) E[X] = a/b

    R equivalent: X ~ g(shape=a,rate=b) OR

    X ~ g(shape=a,scale=1/b)

  • MARSS Dev Site

    MARSS is an R package to fit mulitvariate autoregressive state-space (MARSS) models with Gaussian errors to multivariate time series data.  Developers: Eli Holmes, Eric Ward, Mark Scheuerell and Kellie Wills. 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. To see what's coming in the next version, click NEWS in the files.

    To install patches
    source("patchfile.r") #replace with actual file name
    library(R.utils) #install if needed
    #replace patch_fun with function name in patchfile.r
    reassignInPackage("patch_fun", pkgName="MARSS", patch_fun)
    To install the development version
    library(devtools)
    install_url("https://fishbox.nwfsc.noaa.gov/zip/e2holmes/MARSS%20Dev%20Site/MARSS_source.zip")

Projects for multivariate autoregressive:

1-2 of 2 shown   (1 visible only to FishBox members).    
    
1  

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