getFitted: Get fitted/predicted values

In DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models

Get fitted/predicted values

Description

Wrapper to get the fitted/predicted response of model at the response scale.

Usage

getFitted(object, ...)

## Default S3 method:
getFitted(object, ...)

## S3 method for class 'gam'
getFitted(object, ...)

## S3 method for class 'HLfit'
getFitted(object, ...)

## S3 method for class 'MixMod'
getFitted(object, ...)

## S3 method for class 'phylolm'
getFitted(object, ...)

## S3 method for class 'phyloglm'
getFitted(object, ...)

Arguments

object	A fitted model.
...	Additional parameters to be passed on, usually to the simulate function of the respective model class.

Details

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 random effects (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 RE estimates (because of https://github.com/florianhartig/DHARMa/issues/43), which corresponds to re-form = ~0 in lme4.

Author(s)

Florian Hartig

See Also

getObservedResponse, getSimulations, getRefit, getFixedEffects

Examples

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))

DHARMa documentation built on Oct. 18, 2024, 5:09 p.m.