Description: 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>.
reshape2, PPCI, clustrd, smacof, rgl,prclust, dendextend,
moments,prabclus, VarSelLCM, sparcl, mixtools, HDclassif,

clustvarsel, yardstick, knitr, rmarkdown, igraph, leiden,

Title: A Collection of Fluorescence Fluctuation Spectroscopy Methods
Author: Raul Pinto Camara, Adan Guerrero.
Maintainer: Raul Pinto Camara <vasto.lorde.rp@gmail.com>
Description: A set of tools for fluorescence fluctuation spectroscopy data analysis performance is provided in this package.
It includes techniques such as single-point fluorescence correlation spectroscopy, autocorrelation and pair correlation functions, number & brightness (raster line scan) and a novel method recently developed by Hinde and co-workers, pair correlation of molecular brightness.
A set of simulations and real experimental data is used for the examples of each function provided in this package.
For an in-depth description of the basics behind each function here included and a detailed step-by-step guide on how to use them on your own data, please refer to the Supplementary Material file provided at (<https://github.com/RPintoC/FCSlib_Sup>).
R.A. Migueles-Ramirez, A.G. Velasco-Felix, R. Pinto-Camara, C.D. Wood, A. Guerrero (2017, ISBN-13:978-84-942134-9-6).
Hinde, E., Pandzic, E., Yang, Z., Ng, I. H., Jans, D. A., Bogoyevitch, M. A., Gratton, E. & Gaus, K. (2016) <doi:10.1038/ncomms11047>.