DHARMa (version 0.3.3.0)

getSimulations: Get model simulations

Description

Wrapper to simulate from a fitted model

Usage

getSimulations(object, nsim = 1, type = c("normal", "refit"), ...)
# S3 method for default
getSimulations(object, nsim = 1, type = c("normal", "refit"), ...)
# S3 method for negbin
getSimulations(object, nsim = 1, type = c("normal", "refit"), ...)
# S3 method for lmerMod
getSimulations(object, nsim = 1, type = c("normal", "refit"), ...)
# S3 method for glmmTMB
getSimulations(object, nsim = 1, type = c("normal", "refit"), ...)
# S3 method for HLfit
getSimulations(object, nsim = 1, type = c("normal", "refit"), ...)

Arguments

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

Value

a matrix with simulations

Details

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.

See Also

getObservedResponse, getRefit, getFixedEffects, getFitted

Examples

# NOT RUN {
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))
# }