Directional (version 6.7)

Prediction in discriminant analysis based on ESAG distribution: Prediction of a new observation using discriminant analysis based on ESAG distribution

Description

Prediction of a new observation using discriminant analysis based on ESAG distribution.

Usage

esagda.pred(ynew, y, ina)

Value

A vector with the predicted group of each new observation.

Arguments

ynew

The new observation(s) (unit vector(s)) whose group is to be predicted.

y

A data matrix with unit vectors, i.e. spherical directional data.

ina

A vector indicating the groups of the data y.

Author

Michail Tsagris.

R implementation and documentation: Michail Tsagris .

Details

Prediction of the class of a new spherical vector assuming ESAG distribution.

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.

Paine P.J., Preston S.P. and Tsagris M. and Wood A.T.A. (2018). An Elliptically Symmetric Angular Gaussian Distribution. Statistics and Computing, 28(3): 689--697.

Mardia K. V. and Jupp P. E. (2000). Directional statistics. Chicester: John Wiley & Sons.

See Also

esag.da, vmfda.pred, dirknn, knn.reg

Examples

m1 <- rnorm(3)
m2 <- rnorm(3) + 0.5
y <- rbind( rvmf(100, m1, 3), rvmf(80, m2, 5) )
ina <- c( rep(1,100), rep(2, 80) )
ynew <- rbind(rvmf(10, m1, 10), rvmf(10, m2, 5))
id <- rep(1:2, each = 10)
g <- esagda.pred(ynew, y, ina)
table(id, g)