predict method for MxModel objects
predict 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.
Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.