predict.matrixlda {MixMatrix} | R Documentation |
Classify matrix variate observations in conjunction with matrixlda
.
## S3 method for class 'matrixlda' predict(object, newdata, prior = object$prior, ...)
object |
object of class |
newdata |
array or list of new observations to be classified.
If newdata is missing, an attempt will be made to retrieve the
data used to fit the |
prior |
The prior probabilities of the classes, by default the
proportions in the training set or what was set in the call to
|
... |
arguments based from or to other methods |
This function is a method for the generic function predict()
for
class "matrixlda
". It can be invoked by calling predict(x)
for
an object x
of the appropriate class.
Returns a list containing the following components:
class
The MAP classification (a factor)
posterior
posterior probabilities for the classes
matrixlda
, matrixqda
, and matrixmixture
set.seed(20180221) # construct two populations of 3x4 random matrices with different means A <- rmatrixnorm(30,mean=matrix(0,nrow=3,ncol=4)) B <- rmatrixnorm(30,mean=matrix(1,nrow=3,ncol=4)) C <- array(c(A,B), dim=c(3,4,60)) #combine together groups <- c(rep(1,30),rep(2,30)) # define groups prior <- c(.5,.5) # set prior D <- matrixlda(C, groups, prior) predict(D)$posterior[1:10,]