Indirect method for the estimation of reference intervals (RIs)
    using Real-World Data ('RWD') and methods for comparing and verifying RIs.
    Estimates RIs by applying advanced statistical methods to routine
    diagnostic test measurements, which include both pathological and
    non-pathological samples, to model the distribution of non-pathological
    samples. This distribution is then used to derive reference intervals
    and support RI verification, i.e., deciding if a specific RI is suitable
    for the local population. The package also provides functions for
    printing and plotting algorithm results. See ?refineR for a detailed
    description of features. Version 1.0 of the algorithm is described in
    'Ammer et al. (2021)' <doi:10.1038/s41598-021-95301-2>. Additional
    guidance is in 'Ammer et al. (2023)' <doi:10.1093/jalm/jfac101>. The
    verification method is described in 'Beck et al. (2025)'
    <doi:10.1515/cclm-2025-0728>.

These functions take a character vector as input, identify and 
  cluster similar values, and then merge clusters together so their values 
  become identical. The functions are an implementation of the key collision 
  and ngram fingerprint algorithms from the open source tool Open Refine 
  <https://openrefine.org/>. More info on key collision and ngram fingerprint 
  can be found here <https://openrefine.org/docs/technical-reference/clustering-in-depth>.

Reallocating the respective lessons by hours (respecting the 
    constraints induced by the existence of coupled lessons) so that 
    the total number of gaps is as small as possible.

Fits measurement error models using Monte Carlo Expectation Maximization (MCEM). For specific details on the methodology, see: Greg C. G. Wei & Martin A. Tanner (1990) A Monte Carlo Implementation of the EM Algorithm and the Poor Man's Data Augmentation Algorithms, Journal of the American Statistical Association, 85:411, 699-704 <doi:10.1080/01621459.1990.10474930> For more examples on measurement error modelling using MCEM, see the 'RMarkdown' vignette: "'refitME' R-package tutorial".