R/matnormlda.R
predict.matrixqda.Rd
Classify matrix variate observations in conjunction with matrixqda
.
# S3 method for matrixqda predict(object, newdata, prior = object$prior, ...)
object | object of class |
---|---|
newdata | array or list of new observations to be classified.
If newdata is missing, an attempt will be made to retrieve the
data used to fit the |
prior | The prior probabilities of the classes, by default the
proportions in the training set or what was set in the call to
|
... | arguments based from or to other methods |
Returns a list containing the following components:
class
The MAP classification (a factor)
posterior
posterior probabilities for the classes
This function is a method for the generic function predict()
for
class "matrixqda
". It can be invoked by calling predict(x)
for
an object x
of the appropriate class.
set.seed(20180221) # construct two populations of 3x4 random matrices with different means A <- rmatrixnorm(30, mean = matrix(0, nrow = 3, ncol = 4)) B <- rmatrixnorm(30, mean = matrix(1, nrow = 3, ncol = 4)) C <- array(c(A, B), dim = c(3, 4, 60)) # combine together groups <- c(rep(1, 30), rep(2, 30)) # define groups prior <- c(.5, .5) # set prior D <- matrixqda(C, groups, prior) # fit model predict(D)$posterior[1:10, ] # predict, show results of first 10 #> [,1] [,2] #> [1,] 0.9999992 8.354945e-07 #> [2,] 0.6689069 3.310931e-01 #> [3,] 0.9999807 1.934361e-05 #> [4,] 0.9999978 2.172959e-06 #> [5,] 0.9988560 1.144023e-03 #> [6,] 0.8339787 1.660213e-01 #> [7,] 0.9999852 1.481745e-05 #> [8,] 0.9999996 4.176989e-07 #> [9,] 0.9167050 8.329505e-02 #> [10,] 0.9869554 1.304462e-02 ## S3 method for class "matrixqda"