The 1311 time series from the tourism forecasting competition conducted in 2010 and described in Athanasopoulos et al. (2011) <DOI:10.1016/j.ijforecast.2010.04.009>.

A set of tools for processing and modeling high-throughput and
    high-content chemical screening data. The package was developed for the
    the chemical screening data generated by the US EPA ToxCast program, but
    can be used for diverse chemical screening efforts.

Performs the basic concentration response curve fitting used 
    in the 'tcpl' package. It is a substitute for the original tcplFit() function 
    (and sub-functions) and allows a wider variety of concentration-response models. 
    All of the models included in the 'BMDExpress' package are now part of this package,
    and the output includes a calculation of the bmd (Benchmark Dose or concentration) 
    value.

Enables the computation of the 'two cut-points with maximum odds ratio (OR)
    value method' for data analysis, particularly suited for binary classification
    tasks. Users can identify optimal cut-points in a continuous variable by
    maximizing the odds ratio while maintaining an equal risk level, useful for
    tasks such as medical diagnostics, risk assessment, or predictive modeling.

The 'twelvedata' REST service offers access to current and historical
 data on stocks, standard as well as digital 'crypto' currencies, and other financial
 assets covering a wide variety of course and time spans. See <https://twelvedata.com/>
 for details, to create an account, and to request an API key for free-but-capped access
 to the data.

Tools for the statistical analysis of persistent homology and for
    density clustering. For that, this package provides an R interface for the
    efficient algorithms of the C++ libraries 'GUDHI' <https://project.inria.fr/gudhi/software/>, 'Dionysus' <https://www.mrzv.org/software/dionysus/>, and 'PHAT' <https://bitbucket.org/phat-code/phat/>. This package also implements the methods in Fasy et al. (2014) <doi:10.1214/14-AOS1252> and Chazal et al. (2014) <doi:10.1145/2582112.2582128>  for analyzing the statistical significance of persistent homology features.