Prediction of a new observation using discriminant analysis based on von Mises-Fisher distribution
Prediction of the class of a new observation using discriminant analysis based on von Mises-Fisher distribution.
vmfda.pred(xnew, x, ina)
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. |
Discriminant analysis assuming von Mises-Fisher distributions.
A vector with the predicted group of each new observation.
Michail Tsagris.
R implementation and documentation: Michail Tsagris mtsagris@uoc.gr.
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.
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)
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