| Prediction in discriminant analysis based on von Mises-Fisher distribution {Directional} | R Documentation |
Prediction of a new observation using discriminant analysis based on von Mises-Fisher distribution
Description
Prediction of the class of a new observation using discriminant analysis based on von Mises-Fisher distribution.
Usage
vmfda.pred(xnew, x, ina)
Arguments
xnew |
The new observation(s) (unit vector(s)) whose group is to be predicted. |
x |
A data matrix with unit vectors, i.e. directional data. |
ina |
A vector indicating the groups of the data x. |
Details
Discriminant analysis assuming von Mises-Fisher distributions.
Value
A vector with the predicted group of each new observation.
Author(s)
Michail Tsagris.
R implementation and documentation: Michail Tsagris mtsagris@uoc.gr.
References
Tsagris M. and Alenazi A. (2019). Comparison of discriminant analysis methods on the sphere. Communications in Statistics: Case Studies, Data Analysis and Applications, 5(4), 467–491.
Morris J. E. and Laycock P. J. (1974). Discriminant analysis of directional data. Biometrika, 61(2): 335–341.
See Also
vmf.da, mixvmf.mle, dirknn, knn.reg
Examples
m1 <- rnorm(5)
m2 <- rnorm(5)
x <- rbind( rvmf(100, m1, 5), rvmf(80, m2, 10) )
ina <- c( rep(1,100), rep(2, 80) )
y <- rbind(rvmf(10, m1, 10), rvmf(10, m2, 5))
id <- rep(1:2, each = 10)
g <- vmfda.pred(y, x, ina)
table(id, g)