Implements indices of qualitative variation proposed by Wilcox
    (1973).

These functions use data augmentation and Bayesian techniques for the assessment of single-member and incomplete ensembles of climate projections. It provides unbiased estimates of climate change responses of all simulation chains and of all uncertainty variables. It additionally propagates uncertainty due to missing information in the estimates.
  - Evin, G., B. Hingray, J. Blanchet, N. Eckert, S. Morin, and D. Verfaillie. (2019) <doi:10.1175/JCLI-D-18-0606.1>.

Implements quantile-based discriminant analysis (QuanDA) for
    imbalanced classification in high-dimensional, low-sample-size settings.
    The method fits penalized quantile regression directly on discrete class labels and
    tunes the quantile level to reflect class imbalance.

Functions for interacting directly with the Quandl API to offer data in a number of formats usable in R, downloading a zip with all data from a Quandl database, and the ability to search. This R package uses the Quandl API. For more information go to <https://docs.quandl.com>. For more help on the package itself go to <https://www.quandl.com/tools/r>.

Values different types of assets and calibrates discount curves 
    for quantitative financial analysis. It covers fixed coupon assets, 
    floating note assets, interest and cross currency swaps with different 
    payment frequencies. Enables the calibration of spot, instantaneous forward 
    and basis curves, making it a powerful tool for accurate and flexible bond 
    valuation and curve generation. The valuation and calibration techniques 
    presented here are consistent with industry standards and incorporates 
    author's own calculations. Tuckman, B., Serrat, A. (2022, ISBN: 978-1-119-83555-4).

Non-parametric methods as local normal regression, polynomial local regression and penalized cubic B-splines regression are used to estimate quantiles curves. See Fan and Gijbels (1996) <doi:10.1201/9780203748725> and Perperoglou et al.(2019) <doi:10.1186/s12874-019-0666-3>.