Functions to simplify the process of preparing event and transaction for cohort analysis.

Estimate survival using data mapped to the Observational Medical Outcomes Partnership common data model. Survival can be estimated based on user-defined study cohorts.

Calculating crude sequence ratio, adjusted sequence ratio and 
    confidence intervals using data mapped to the Observational Medical 
    Outcomes Partnership Common Data Model.

Functions to make lifetables and to calculate hazard function estimate using Poisson regression model with splines. Includes function to draw simple flowchart of cohort study. Function boxesLx() makes boxes of transition rates between states. It utilizes 'Epi' package 'Lexis' data.

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/>.

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.