function of a univariate or a multivariate time series. Both versions
of biased and unbiased estimators of distance covariance and correlation are provided.
Test statistics for testing pairwise independence are also implemented.

person( "Maria", "Pitsillou", role = c("aut", "cph"), email = "pitsillou.maria@ucy.ac.cy" ),
Description: Computing and plotting the distance covariance and correlation function of a univariate or a multivariate time series. Both versions of biased and unbiased estimators of distance covariance and correlation are provided. Test statistics for testing pairwise independence are also implemented. Some data sets are also included. References include:
a) Edelmann Dominic, Fokianos Konstantinos and Pitsillou Maria (2019). An Updated Literature Review of Distance Correlation and Its Applications to Time Series. International Statistical Review, 87(2): 237--262. <doi:10.1111/insr.12294>.
b) Fokianos Konstantinos and Pitsillou Maria (2018). Testing independence for multivariate time series via the auto-distance correlation matrix. Biometrika, 105(2): 337--352. <doi:10.1093/biomet/asx082>.
c) Fokianos Konstantinos and Pitsillou Maria (2017). Consistent testing for pairwise dependence in time series. Technometrics, 59(2): 262--270. <doi:10.1080/00401706.2016.1156024>.
d) Pitsillou Maria and Fokianos Konstantinos (2016). dCovTS: Distance Covariance/Correlation for Time Series. R Journal, 8(2):324-340. <doi:10.32614/RJ-2016-049>.
Imports: dcov, doParallel, foreach, parallel, Rfast, Rfast2

Title: Genetic Algorithm with Incomplete Dominance for Feature
Maintainer: Nicolae Teodor Melita <nt_melita@yahoo.com>
Description: Feature selection from high dimensional data using a diploid
genetic algorithm with Incomplete Dominance for genotype to phenotype mapping
and Random Assortment of chromosomes approach to recombination.
Depends: R (>= 3.3.1), Biobase, MLInterfaces
Imports: genefilter, ALL, grDevices, graphics, stats, utils

Title: Independence Testing via Hilbert Schmidt Independence Criterion
Description: Contains an implementation of the
d-variable Hilbert Schmidt independence criterion
and several hypothesis tests based on it.