| Cross validation with Purkayastha discrminant analysis {Directional} | R Documentation |
Cross validation for estimating the classification rate of a discrminant analysis for directional data assuming a Purkayastha distribution
Description
Cross validation for estimating the classification rate of a discrminant analysis for directional data assuming a Purkayastha distribution.
Usage
purka.da(y, ina, fraction = 0.2, R = 100, seed = NULL)
Arguments
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 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
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
Examples
x <- rvmf(100, rnorm(3), 15)
ina <- rep(1:2, each = 50)
purka.da(x, ina, fraction = 0.2, R = 50)