Computes the third multivariate cumulant of either the raw, centered or standardized data. Computes the main measures of multivariate skewness, together with their bootstrap distributions. Finally, computes the least skewed linear projections of the data.

Implements two versions of the algorithm namely: stochastic and batch. The package determines also the best number of clusters and offers to the user the best clustering scheme from different results.

The multispatial convergent cross mapping algorithm can be used as a test for causal associations between pairs of processes represented by time series. This is a combination of convergent cross mapping (CCM), described in Sugihara et al., 2012, Science, 338, 496-500, and dew-drop regression, described in Hsieh et al., 2008, American Naturalist, 171, 71–80. The algorithm allows CCM to be implemented on data that are not from a single long time series. Instead, data can come from many short time series, which are stitched together using bootstrapping.

Algorithms to build set partitions and commutator matrices and their use in the 
    construction of multivariate d-Hermite polynomials;  estimation and derivation of theoretical  vector moments and vector
    cumulants  of multivariate distributions; conversion formulae for multivariate moments and cumulants. Applications to
    estimation and derivation of multivariate measures of skewness and kurtosis;  estimation and derivation of asymptotic 
    covariances for d-variate Hermite polynomials, multivariate moments and cumulants and measures of skewness and kurtosis.
    The formulae implemented are discussed in Terdik (2021, ISBN:9783030813925), "Multivariate Statistical Methods".

Implements multitaper spectral analysis using discrete prolate spheroidal sequences (Slepians) and sine tapers. It includes an adaptive weighted multitaper spectral estimate, a coherence estimate, Thomson's Harmonic F-test, and complex demodulation. The Slepians sequences are generated efficiently using a tridiagonal matrix solution, and jackknifed confidence intervals are available for most estimates. This package is an implementation of the method described in D.J. Thomson (1982) "Spectrum estimation and harmonic analysis" <doi:10.1109/PROC.1982.12433>.