Directional (version 4.7)

Cross validation with ESAG discrminant analysis: Cross validation for estimating the classification rate of a discrminant analysis for directional data assuming an ESAG distribution

Description

Cross validation for estimating the classification rate of a discrminant analysis for directional data assuming an ESAG distribution.

Usage

esag.da(y, ina, fraction = 0.2, R = 100, seed = FALSE)

Arguments

y

A matrix with the data in Eulcidean coordinates, i.e. unit vectors. The matrix must have three columns, only spherical data are currently supported.

ina

A variable indicating the groupings.

fraction

The fraction of data to be used as test set.

R

The number of repetitions.

seed

If seed is TRUE, the results will always be the same.

Value

A list including:

percent

The estimated percent of correct classification and two estimated standard deviations. The one is the standard devation of the rates and the other is assuming a binomial distribution.

ci

Three types of confidence intervals, the standard one, another one based on the binomial distribution and the third one is the empirical one, which calcualtes the upper and lower 2.5% of the rates.

Details

A repeated cross validation procedure is performed to estimate the rate of correct classification.

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. (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

vmf.da, vmfda.pred, dirknn

Examples

# NOT RUN {
x <- rvmf(100, rnorm(3), 15)
ina <- rep(1:2, each = 50)
esag.da(x, ina, fraction = 0.2, R = 50, seed = FALSE)
# }