Evaluating if values
  of vectors are within different open/closed intervals
  (`x %[]% c(a, b)`), or if two closed
  intervals overlap (`c(a1, b1) %[]o[]% c(a2, b2)`).
  Operators for negation and directional relations also implemented.

Calculates event rates and compares means and variances of groups of interval data corrected for missed arrival observations.

Integration of disparate datasets is needed in order to make efficient use of all available data and thereby address the issues currently threatening biodiversity.
   Data integration is a powerful modeling framework which allows us to combine these datasets together into a single model, yet retain the strengths of each individual dataset.
   We therefore introduce the package, 'intSDM': an R package designed to help ecologists develop a reproducible workflow of integrated species distribution models, using data both provided from the user as well as data obtained freely online.
   An introduction to data integration methods is discussed in Issac, Jarzyna, Keil, Dambly, Boersch-Supan, Browning, Freeman, Golding, Guillera-Arroita, Henrys, Jarvis, Lahoz-Monfort, Pagel, Pescott, Schmucki, Simmonds and O’Hara (2020) <doi:10.1016/j.tree.2019.08.006>.

Contains implementations of
    integrative survival analysis routines, including
    regular Cox cure rate model proposed by
    Kuk and Chen (1992) <doi:10.1093/biomet/79.3.531>
    via an EM algorithm proposed by
    Sy and Taylor (2000) <doi:10.1111/j.0006-341X.2000.00227.x>,
    regularized Cox cure rate model with elastic net penalty following
    Masud et al. (2018) <doi:10.1177/0962280216677748>, and
    Zou and Hastie (2005) <doi:10.1111/j.1467-9868.2005.00503.x>, and
    weighted concordance index for cure models proposed by
    Asano and Hirakawa (2017) <doi:10.1080/10543406.2017.1293082>.

Provides tools for importing, merging, and analysing data from 
  international assessment studies (TIMSS, PIRLS, PISA, ICILS, and PIAAC).

Enum-type representation of vectors and representation
  of intervals, including a method of coercing variables in data frames.