vmfda.pred: Prediction of a new observation using discriminant analysis...

In Directional: A Collection of Functions for Directional Data Analysis

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 [e-mail].

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)

Directional documentation built on Feb. 16, 2023, 8 p.m.