A set of functions allowing to implement the 'SpiceFP' approach
  which is iterative. It involves transformation of functional predictors into
  several candidate explanatory matrices (based on contingency tables), to which
  relative edge matrices with contiguity constraints are associated. Generalized
  Fused Lasso regression are performed in order to identify the best candidate
  matrix, the best class intervals and related coefficients at each iteration.
  The approach is stopped when the maximal number of iterations is reached or
  when retained coefficients are zeros. Supplementary functions allow to get
  coefficients of any candidate matrix or mean of coefficients of many candidates.
  The methods in this package are describing in Girault Gnanguenon Guesse, 
  Patrice Loisel, Bénedicte Fontez, Thierry Simonneau, Nadine Hilgert (2021)
  "An exploratory penalized regression to identify combined effects of functional
  variables -Application to agri-environmental issues" 
  <https://hal.archives-ouvertes.fr/hal-03298977>.

Improves the interpretation of the Standardized Precipitation
    Index under changing climate conditions. The package uses the
    nonstationary approach proposed in Blain et al. (2022)
    <doi:10.1002/joc.7550> to detect trends in rainfall quantities and to
    quantify the effect of such trends on the probability of a drought event
    occurring.

Extracts and summarizes metadata from data frames, including variable names, labels, types, and missing values. Computes compact descriptive statistics, frequency tables, and cross-tabulations to assist with efficient data exploration. Facilitates the identification of missing data patterns and structural issues in datasets. Designed to streamline initial data management and exploratory analysis workflows within 'R'.

Analysis of species limits and DNA barcoding data. Included are functions for generating important summary statistics from DNA barcode data, assessing specimen identification efficacy, testing and optimizing divergence threshold limits, assessment of diagnostic nucleotides, and calculation of the probability of reciprocal monophyly. Additionally, a sliding window function offers opportunities to analyse information across a gene, often used for marker design in degraded DNA studies. Further information on the package has been published in Brown et al (2012) <doi:10.1111/j.1755-0998.2011.03108.x>.