getSimulations {DHARMa} | R Documentation |
Wrapper to simulate from a fitted model
getSimulations(object, nsim = 1, type = c("normal", "refit"), ...) ## Default S3 method: getSimulations(object, nsim = 1, type = c("normal", "refit"), ...) ## S3 method for class 'negbin' getSimulations(object, nsim = 1, type = c("normal", "refit"), ...) ## S3 method for class 'lmerMod' getSimulations(object, nsim = 1, type = c("normal", "refit"), ...) ## S3 method for class 'glmmTMB' getSimulations(object, nsim = 1, type = c("normal", "refit"), ...) ## S3 method for class 'HLfit' getSimulations(object, nsim = 1, type = c("normal", "refit"), ...) ## S3 method for class 'MixMod' getSimulations(object, nsim = 1, type = c("normal", "refit"), ...)
object |
a fitted model |
nsim |
number of simulations |
type |
if simulations should be prepared for getQuantile or for refit |
... |
additional parameters to be passed on, usually to the simulate function of the respective model class |
The purpose of this wrapper for for the simulate function is to return the simulations from a model in a standardized way
The function is a wrapper for for the simulate function is to return the simulations from a model in a standardized way.
Note: if the model was fit with weights, the function will throw a warning if used with a model class whose simulate function does not include the weightsi in the simulations. Note that the results may or may not be appropriate in this case, depending on how you use the weights.
a matrix with simulations
Florian Hartig
getObservedResponse
, getRefit
, getFixedEffects
, getFitted
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))