Numerical integration of cause-specific survival curves to arrive at cause-specific cumulative incidence functions,
  with three usage modes: 1) Convenient API for parametric survival regression followed by competing-risk analysis, 2) API for
  CFC, accepting user-specified survival functions in R, and 3) Same as 2, but accepting survival functions in C++. For 
  mathematical details and software tutorial, see Mahani and Sharabiani (2019) <DOI:10.18637/jss.v089.i09>.

Package for the analysis of categorical functional data.
  The main purpose is to compute an encoding (real functional variable) for each state <doi:10.3390/math9233074>.
  It also provides functions to perform basic statistical analysis on categorical functional data.

Provides a set of functions for counterfactual decomposition (cfdecomp). The functions available in this package decompose differences in an outcome attributable to a mediating variable (or sets of mediating variables) between groups based on counterfactual (causal inference) theory. By using Monte Carlo (MC) integration (simulations based on empirical estimates from multivariable models) we provide added flexibility compared to existing (analytical) approaches, at the cost of computational power or time. The added flexibility means that we can decompose difference between groups in any outcome or and with any mediator (any variable type and distribution). See Sudharsanan & Bijlsma (2019) <doi:10.4054/MPIDR-WP-2019-004> for more information.

A simple, fast algorithm to find the neighbors and similarities of users in user-based filtering systems,
             to break free from the complex computation of existing similarity formulas and the ability to solve big data.

This project provides a group of new functions to calculate
    the outputs of the two main components of the Canadian Forest Fire
    Danger Rating System (CFFDRS) Van Wagner and Pickett (1985)
    <https://cfs.nrcan.gc.ca/publications?id=19973>) at various time
    scales: the Fire Weather Index (FWI) System Wan Wagner (1985)
    <https://cfs.nrcan.gc.ca/publications?id=19927> and the Fire Behaviour
    Prediction (FBP) System Forestry Canada Fire Danger Group (1992)
    <https://cfs.nrcan.gc.ca/pubwarehouse/pdfs/10068.pdf>. Some functions
    have two versions, table and raster based.