predict.MxModel | R Documentation |
predict
method for MxModel
objectspredict
method for MxModel
objects
## S3 method for class 'MxModel'
predict(
object,
newdata = NULL,
interval = c("none", "confidence", "prediction"),
method = c("ML", "WeightedML", "Regression", "Kalman"),
level = 0.95,
type = c("latent", "observed"),
...
)
object |
an MxModel object from which predictions are desired |
newdata |
an optional |
interval |
character indicating what kind of intervals are desired. 'none' gives no intervals, 'confidence', gives confidence intervals, 'prediction' gives prediction intervals. |
method |
character the method used to create the predictions. See details. |
level |
the confidence or predictions level, ignored if not using intervals |
type |
character the type of thing you want predicted: latent variables or manifest variables. |
... |
further named arguments |
The newdata
argument is either a data.frame
or MxData
object. In the latter case is replaces the data in the top level model. In the former case, it is passed as the observed
argument of mxData
with type='raw'
and must accept the same further arguments as the data in the model passed in the object
argument.
The available methods for prediction are 'ML', 'WeightedML', 'Regression', and 'Kalman'. See the help page for mxFactorScores
for details on the first three of these. The 'Kalman' method uses the Kalman filter to create predictions for state space models.
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