GR2 is a generic function that calculates and displays the
generalised R2 value for fitted
an object of class glmssn
The generalised R2 value, or ‘coefficient of determination’, lies somewhere between 0 and 1, and is a general measure of the predictive power of a model. In this instance, it relates to the proportion of the variability in the data that is explained by the fixed effects.
a numeric value equal to the GR2 for the specified
Jay Ver Hoef support@SpatialStreamNetworks.com
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library(SSN) #for examples, copy MiddleFork04.ssn directory to R's temporary directory copyLSN2temp() # NOT RUN # Create a SpatialStreamNetork object that also contains prediction sites #mf04p <- importSSN(paste0(tempdir(),'/MiddleFork04.ssn'), # predpts = "pred1km", o.write = TRUE) #use mf04p SpatialStreamNetwork object, already created data(mf04p) #for examples only, make sure mf04p has the correct path #if you use importSSN(), path will be correct mf04p <- updatePath(mf04p, paste0(tempdir(),'/MiddleFork04.ssn')) # get some model fits stored as data objects data(modelFits) #NOT RUN use this one #fitSp <- glmssn(Summer_mn ~ ELEV_DEM + netID, # ssn.object = mf04p, EstMeth = "REML", family = "Gaussian", # CorModels = c("Exponential.tailup","Exponential.taildown", # "Exponential.Euclid"), addfunccol = "afvArea") #for examples only, make sure fitSp has the correct path #if you use importSSN(), path will be correct fitSp$ssn.object <- updatePath(fitSp$ssn.object, paste0(tempdir(),'/MiddleFork04.ssn')) GR2(fitSp)
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