| Prediction in discriminant analysis based on Purkayastha distribution {Directional} | R Documentation |
Prediction of a new observation using discriminant analysis based on Purkayastha distribution
Description
Prediction of a new observation using discriminant analysis based on Purkayastha distribution.
Usage
purkada.pred(ynew, y, ina)
Arguments
ynew |
The new observation(s) whose group is to be predicted. A numerical vector with data expressed in radians, or a matrix with two columns (cos and sin) for circular data. Or a matrix with 3 columns (unit vectors) for spherical data. |
y |
A numerical vector with data expressed in radians, or a matrix with two columns (cos and sin) for circular data. Or a matrix with 3 columns (unit vectors) for spherical data. |
ina |
A vector indicating the groups of the data y. |
Details
Prediction of the class of a new spherical vector assuming ESAG distribution.
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
Purkayastha S. (1991). A Rotationally Symmetric Directional Distribution: Obtained through Maximum Likelihood Characterization. The Indian Journal of Statistics, Series A, 53(1): 70–83
Cabrera J. and Watson G. S. (1990). On a spherical median related distribution. Communications in Statistics-Theory and Methods, 19(6): 1973–1986.
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 <- purkada.pred(ynew, y, ina)
table(id, g)