Cross validation for estimating the classification rate of a discrminant analysis for directional data assuming an ESAG distribution.
esag.da(y, ina, fraction = 0.2, R = 100, seed = NULL)A list including:
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.
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.
A matrix with the data in Eulcidean coordinates, i.e. unit vectors. The matrix must have three columns, only spherical data are currently supported.
A variable indicating the groupings.
The fraction of data to be used as test set.
The number of repetitions.
You can specify your own seed number here or leave it NULL.
Michail Tsagris.
R implementation and documentation: Michail Tsagris mtsagris@uoc.gr.
A repeated cross validation procedure is performed to estimate the rate of correct classification.
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.
vmf.da, vmfda.pred, dirknn
x <- rvmf(100, rnorm(3), 15)
ina <- rep(1:2, each = 50)
esag.da(x, ina, fraction = 0.2, R = 50)
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