| mclustDAtest {mclust} | R Documentation |
Testing phase for MclustDA discriminant analysis.
mclustDAtest(data, models)
data |
A numeric vector, matrix, or data frame of observations to be classified. |
models |
A list of MCLUST-style models including parameters, usually the
result of applying mclustDAtrain to some training data.
|
A matrix in which the [i,j]th entry is the
density for that test observation i in the model for class j.
C. Fraley and A. E. Raftery (2002a). Model-based clustering, discriminant analysis, and density estimation. Journal of the American Statistical Association 97:611-631. See http://www.stat.washington.edu/mclust.
C. Fraley and A. E. Raftery (2002b). MCLUST:Software for model-based clustering, density estimation and discriminant analysis. Technical Report, Department of Statistics, University of Washington. See http://www.stat.washington.edu/mclust.
summary.mclustDAtest,
mclustDAtrain
n <- 250 ## create artificial data
set.seed(0)
x <- rbind(matrix(rnorm(n*2), n, 2) %*% diag(c(1,9)),
matrix(rnorm(n*2), n, 2) %*% diag(c(1,9))[,2:1])
xclass <- c(rep(1,n),rep(2,n))
## Not run:
par(pty = "s")
mclust2Dplot(x, classification = xclass, type="classification", ask=FALSE)
## End(Not run)
odd <- seq(1, 2*n, 2)
train <- mclustDAtrain(x[odd, ], labels = xclass[odd]) ## training step
summary(train)
even <- odd + 1
test <- mclustDAtest(x[even, ], train) ## compute model densities
summary(test)$class ## classify training set