Functions to reconstruct sessions from web log or other user trace data
             and calculate various metrics around them, producing tabular,
             output that is compatible with 'dplyr' or 'data.table' centered processes.

The Rearrangement Correlation Coefficient is an adjusted version of Pearson's 
    correlation coefficient that accurately measures monotonic dependence 
    relationships, including both linear and nonlinear associations. This 
    method addresses the underestimation problem of classical correlation 
    coefficients in nonlinear monotonic scenarios through improved statistical 
    bounds derived from rearrangement inequalities. For more details, 
    see Ai (2024) <doi:10.52202/079017-1180>.

A lightweight toolkit to validate new observations when computing
    their predictions with a predictive model. The validation process 
    consists of two steps: (1) record relevant statistics and meta data of the
    variables in the original training data for the predictive model and
    (2) use these data to run a set of basic validation tests on the new set of 
    observations.

Provides functions for linking and deduplicating data sets.
  Methods based on a stochastic approach are implemented as well as 
  classification algorithms from the machine learning domain. For details, 
  see our paper "The RecordLinkage Package: Detecting Errors in Data" 
  Sariyar M / Borg A (2010) <doi:10.32614/RJ-2010-017>.

Functions for generating k-record values and k-record
        times

Statistical tools based on the probabilistic properties of the 
  record occurrence in a sequence of independent and identically distributed 
  continuous random variables. In particular, tools to prepare a time series 
  as well as distribution-free trend and change-point tests and graphical 
  tools to study the record occurrence. Details about the implemented tools 
  can be found in Castillo-Mateo et al. (2023a) <doi:10.18637/jss.v106.i05> 
  and Castillo-Mateo et al. (2023b) <doi:10.1016/j.atmosres.2023.106934>.