# esagda.pred: Prediction of a new observation using discriminant analysis... In Directional: A Collection of Functions for Directional Data Analysis

 Prediction in discriminant analysis based on ESAG distribution R Documentation

## 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)
```

### 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.

### 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

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., Tsagris M. and Wood A.T.A. (2017). 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.

```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)
```

Directional documentation built on Jan. 12, 2023, 1:12 a.m.