Computes the cosine-correlation coefficient for measuring the degree of linear dependence among variables in a multidimensional context. The package implements the generalized cosine-correlation theorem for p-1 variables, providing a quantitative assessment of interrelationships within experimental frameworks. This methodology extends classical correlation measures to higher-dimensional spaces using a dimensional exploration approach based on time scale calculus.
The cosCorr package implements the cosine-correlation coefficient, a novel measure for assessing the degree of linear dependence among variables in a multidimensional context.
install.packages("cosCorr")
library(cosCorr)
# Simple example
x <- c(0, 2, 3, 4)
rho <- cosCorr(x)
print(rho)
The cosine-correlation coefficient is defined as:
rho = [(p-1) * prod(|t_i|)] / sum(|t_i|^(p-1))
where t_1 = 0 and t_2, ..., t_p are the variables in the system.
Mehmet Niyazi Cankaya
Faculty of Applied Sciences
Department of International Trading and Finance
Usak University, Usak, Turkey
Email: [email protected]
Cankaya, M. N. (2025). Derivatives through Probes in Regular Geometric Objects: A Dimensional Exploration for qqq-Sets in Time Scale Calculus. Fractals, in printing progress.