A streamlined cross-referencing system for R Markdown documents
    generated with 'knitr'. R Markdown is  an authoring format for generating
    dynamic content from R. 'kfigr' provides a hook for anchoring code
    chunks and a function to cross-reference document elements generated from
    said chunks, e.g. figures and tables.

A method for detecting outliers with a Kalman filter on impulsed 
  noised outliers and prediction on cleaned data. 'kfino' is a robust 
  sequential algorithm allowing to filter data with a large number of outliers. 
  This algorithm is based on simple latent linear Gaussian processes as in the 
  Kalman Filter method and is devoted to detect impulse-noised outliers. These 
  are data points that differ significantly from other observations. 'ML' 
  (Maximization Likelihood) and 'EM' (Expectation-Maximization algorithm) 
  algorithms were implemented in 'kfino'. The method is described in full 
  details in the following arXiv e-Print: <arXiv:2208.00961>.

Implementation for Kendall functional principal component analysis. Kendall functional principal component analysis is a robust functional principal component analysis technique for non-Gaussian functional/longitudinal data. The crucial function of this package is KFPCA() and KFPCA_reg(). Moreover, least square estimates of functional principal component scores are also provided. Refer to Rou Zhong, Shishi Liu, Haocheng Li, Jingxiao Zhang. (2021) <arXiv:2102.01286>. Rou Zhong, Shishi Liu, Haocheng Li, Jingxiao Zhang. (2021) <doi:10.1016/j.jmva.2021.104864>.

Implementation for kernel functional partial least squares (KFPLS) method. KFPLS method is developed for functional nonlinear models, and the method does not require strict constraints for the nonlinear structures. The crucial function of this package is KFPLS().

Implements the Kidney Failure Risk Equation
  (KFRE; Tangri and colleagues (2011) <doi:10.1001/jama.2011.451>;
  Tangri and colleagues (2016) <doi:10.1001/jama.2015.18202>) to compute
  2- and 5-year kidney failure risk using 4-, 6-, and 8-variable models.
  Includes helpers to append risk columns to data frames, classify
  chronic kidney disease (CKD) stages and end-stage renal disease (ESRD)
  outcomes, and evaluate and plot model performance.