Increases the ease of implementing a temporally-explicit modeling
    methodology when building ecological niche and species distribution models.
    Provides functions to assist with three major steps of temporally-explicit
    models: (i) preprocessing species and environmental data and generating
    suitable background or pseudoabsence data, (ii) building a niche model and
    generating temporally-explicit predictions from that model, and (iii) model
    postprocessing to explore spatiotemporal trends in model predictions.
    Methodological and theoretical foundations are described in Ingenloff and
    Peterson (2021) <doi:10.1111/2041-210X.13564>, Franklin (2010, ISBN:9780521700023), 
    Peterson et al. (2011, ISBN:9780691136882), Blonder (2018) <doi:10.1111/ecog.03187>, 
    Senay et al. (2013) <doi:10.1371/journal.pone.0071218>, and Li and Zhang (2024) <doi:10.48550/arXiv.2404.05933>.

Analysis and visualization of data from temporal sensory methods, including for temporal check-all-that-apply (TCATA) and temporal dominance of sensations (TDS). Methods are mainly from manuscripts by Castura, J.C., Antúnez, L., Giménez, A., and Ares, G. (2016) <doi:10.1016/j.foodqual.2015.06.017>, Castura, Baker, and Ross (2016) <doi:10.1016/j.foodqual.2016.06.011>, and Pineau et al. (2009) <doi:10.1016/j.foodqual.2009.04.005>.

A collection of methods to estimate parameters of different tempered stable 
  distributions (TSD). Currently, there are seven different tempered stable 
  distributions to choose from: Tempered stable subordinator distribution, 
  classical TSD, generalized classical TSD, normal TSD, modified TSD, rapid 
  decreasing TSD, and Kim-Rachev TSD.
  The package also provides functions to compute density and probability 
  functions and tools to run Monte Carlo simulations.
  This package has already been used for the estimation of tempered stable 
  distributions (Massing (2023) <arXiv:2303.07060>).
  The following references form the theoretical background for various functions
  in this package. References for each function are explicitly listed in its 
  documentation:
  Bianchi et al. (2010) <doi:10.1007/978-88-470-1481-7_4>
  Bianchi et al. (2011) <doi:10.1137/S0040585X97984632>
  Carrasco (2017) <doi:10.1017/S0266466616000025>
  Feuerverger (1981) <doi:10.1111/j.2517-6161.1981.tb01143.x>
  Hansen et al. (1996) <doi:10.1080/07350015.1996.10524656>
  Hansen (1982) <doi:10.2307/1912775>
  Hofert (2011) <doi:10.1145/2043635.2043638>
  Kawai & Masuda (2011) <doi:10.1016/j.cam.2010.12.014>
  Kim et al. (2008) <doi:10.1016/j.jbankfin.2007.11.004>
  Kim et al. (2009) <doi:10.1007/978-3-7908-2050-8_5>
  Kim et al. (2010) <doi:10.1016/j.jbankfin.2010.01.015>
  Kuechler & Tappe (2013) <doi:10.1016/j.spa.2013.06.012>
  Rachev et al. (2011) <doi:10.1002/9781118268070>.