| Cross validation with ESAG discrminant analysis {Directional} | R Documentation |
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 = NULL)
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 |
You can specify your own seed number here or leave it NULL. |
Details
A repeated cross validation procedure is performed to estimate the rate of correct classification.
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. |
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. (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
Examples
x <- rvmf(100, rnorm(3), 15)
ina <- rep(1:2, each = 50)
esag.da(x, ina, fraction = 0.2, R = 50)