| predict.lmdu {lmap} | R Documentation | 
The function predict.lmdu makes predictions for a test/validation set based on a fitted lrmdu model (lmdu with X)
Description
The function predict.lmdu makes predictions for a test/validation set based on a fitted lrmdu model (lmdu with X)
Usage
## S3 method for class 'lmdu'
predict(object, newX, newY = NULL, ...)
Arguments
| object | An  | 
| newX | An N by P matrix with predictor variables for a test/validation set | 
| newY | An N by R matrix with response variables for a test/validation set | 
| ... | additional arguments to be passed. | 
Value
This function returns an object of the class lpca with components:
| Yhat | Predicted values for the test set | 
| devr | Estimated prediction deviance for separate responses | 
| devtot | Estimated prediction deviance for all responses | 
| Brier.r | Estimated Brier score for separate responses | 
| Brier | Estimated Brier score for all responses | 
Examples
## Not run: 
data(dataExample_lpca)
Y = as.matrix(dataExample_lmdu[-c(1:20) , 1:8])
X = as.matrix(dataExample_lmdu[-c(1:20) , 9:13])
newY = as.matrix(dataExample_lmdu[1:20 , 1:8])
newX = as.matrix(dataExample_lmdu[1:20 , 9:13])
# supervised
output = lmdu(Y = Y, X = X, S = 2)
preds = predict(output, newX = newX, newY = newY)
## End(Not run)
[Package lmap version 0.1.2 Index]