canldaRes: Class object used for storing the results of a canonical...
In HiDimDA: High Dimensional Discriminant Analysis

‘predict.canldaRes’ classifies multivariate observations in conjunction with a ‘canldaRes’ object.

‘print.canldaRes’ is the S3 print method for ‘canldaRes’ objects.

‘coef.canldaRes’ is the S3 coef method for ‘canldaRes’ objects.

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## S3 method for class 'canldaRes'
predict(object, newdata, prior=object$prior, grpcodes=NULL, 
nbvrs=ncol(object$scaling), ...)

`object`	An object of class ‘canldaRes’.
`newdata`	Matrix of cases to be classified.
`prior`	The prior probabilities used.
`grpcodes`	Factor with the class codes. Set to 0:k-1 (k being the number of different classes) by default.
`nbvrs`	Number of canonical discriminant variables used for prediction.
`...`	Further arguments passed to or from other methods.

A list with components

`class`	The MAP classification (a factor)
`ZsqDistances`	A matrix with the squared Euclidean distance, in the discriminant space, of each new observation to the group centroids.
`prior`	The prior probabilities used.
`ZsqDprioradj`	The adjustments to squared Euclidean distance, induced by the chosen (or estimated) prior probabilities.
`Z`	A matrix with the values of the canonical discriminant variates.
`Zmeans`	A matrix with the group centroids in the canonical space.