Copula-based imputation methods: parametric and nonparametric algorithms for missing multivariate data through conditional copulas.

Conditional inference procedures for the general independence
             problem including two-sample, K-sample (non-parametric ANOVA),
             correlation, censored, ordered and multivariate problems described
             in <doi:10.18637/jss.v028.i08>.

Extract and monitor price and market cap of 'Cryptocurrencies' from 'Coin Market Cap' <https://coinmarketcap.com/api/>.

Several authors have proposed methods for constructing simultaneous confidence intervals for multinomial proportions. The package implements seven classical approaches—Wilson, Quesenberry and Hurst, Goodman, Wald (with and without continuity correction), Fitzpatrick and Scott, and Sison and Glaz—along with Bayesian methods based on Dirichlet models. Both equal and unequal Dirichlet priors are supported, providing a broad framework for inference, data analysis, and sensitivity evaluation.

Builds the 
  coincident profile proposed by Martinez, W and Nieto, Fabio H and Poncela, P (2016) 
  <doi:10.1016/j.spl.2015.11.008>.
  This methodology studies the relationship between a couple of
  time series based on the the set of turning points of each
  time series. The coincident profile establishes if two time
  series are coincident, or one of them leads the second.

A comprehensive high-level package, for composite indicator construction and analysis. It is a "development environment"
    for composite indicators and scoreboards, which includes utilities for construction (indicator selection, denomination, imputation,
    data treatment, normalisation, weighting and aggregation) and analysis (multivariate analysis, correlation plotting, short cuts for
    principal component analysis, global sensitivity analysis, and more). A composite indicator is completely encapsulated inside a single
    hierarchical list called a "coin". This allows a fast and efficient work flow, as well as making quick copies, testing methodological variations and making comparisons.
    It also includes many plotting options, both statistical (scatter plots, distribution plots) as well as for presenting results.