Wrapper to get the fitted / predicted response of model at the response scale
getFitted(object, ...)# S3 method for default
getFitted(object, ...)
# S3 method for default
getResiduals(object, ...)
# S3 method for gam
getFitted(object, ...)
# S3 method for HLfit
getFitted(object, ...)
# S3 method for MixMod
getFitted(object, ...)
a fitted model
additional parameters to be passed on, usually to the simulate function of the respective model class
Florian Hartig
The purpose of this wrapper is to standardize extract the fitted values, which is implemented via predict(model, type = "response") for most model classes.
If you implement this function for a new model class, you should include an option to modifying which REs are included in the predictions. If this option is not available, it is essential that predictions are provided marginally / unconditionally, i.e. without the random effect estimates (because of https://github.com/florianhartig/DHARMa/issues/43), which corresponds to re-form = ~0 in lme4
getObservedResponse, getSimulations, getRefit, getFixedEffects
testData = createData(sampleSize = 400, family = gaussian())
fittedModel <- lm(observedResponse ~ Environment1 , data = testData)
# response that was used to fit the model
getObservedResponse(fittedModel)
# predictions of the model for these points
getFitted(fittedModel)
# extract simulations from the model as matrix
getSimulations(fittedModel, nsim = 2)
# extract simulations from the model for refit (often requires different structure)
x = getSimulations(fittedModel, nsim = 2, type = "refit")
getRefit(fittedModel, x[[1]])
getRefit(fittedModel, getObservedResponse(fittedModel))
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