Provides a  collection of functions to 
	manage, to investigate and to analyze bivariate financial returns by  
	Copulae. Included are the families of Archemedean, Elliptical, 
	Extreme Value, and Empirical Copulae.

A function composition operator to chain a series of calls into a single function, mimicking the math notion of (f o g o h)(x) = h(g(f(x))). Inspired by 'pipeOp' ('|>') since R4.1 and 'magrittr pipe' ('%>%'), the operator build a pipe without putting data through, which is best for anonymous function accepted by utilities such as apply() and lapply().

Over sixty clustering algorithms are provided in this package with consistent input and output, which enables the user to try out algorithms swiftly. Additionally, 26 statistical approaches for the estimation of the number of clusters as well as the mirrored density plot (MD-plot) of clusterability are implemented. The packages is published in Thrun, M.C., Stier Q.: "Fundamental Clustering Algorithms Suite" (2021), SoftwareX, <DOI:10.1016/j.softx.2020.100642>. Moreover, the fundamental clustering problems suite (FCPS) offers a variety of clustering challenges any algorithm should handle when facing real world data, see Thrun, M.C., Ultsch A.: "Clustering Benchmark Datasets Exploiting the Fundamental Clustering Problems" (2020), Data in Brief, <DOI:10.1016/j.dib.2020.105501>.

A fold change rank based method is presented to search for genes with changing
             expression and to detect recurrent chromosomal copy number aberrations. This 
             method may be useful for high-throughput biological data (micro-array, sequencing, ...).
             Probabilities are associated with genes or probes in the data set and there is no
             problem of multiple tests when using this method. For array-based comparative genomic
             hybridization data, segmentation results are obtained by merging the significant
             probes detected.

Provides a collection of utility functions for manipulating and analyzing factor vectors in R. It offers tools for filtering, splitting, combining, and reordering factor levels based on various criteria. The package is designed to simplify common tasks in categorical data analysis, making it easier to work with factors in a flexible and efficient manner.