A method to calculate the distance to the climatic tree line
    for large data sets of coordinates (World Geodetic System 1984) with 
    geographical uncertainty. The default thresholds and the treeline definition
    is based on Paulsen and Körner (2014) <doi:10.1007/s00035-014-0124-0>, users
    are free to decide what climate layers they would like to use.

Provides R access to election results data. Wraps elex (https://github.com/newsdev/elex/), a Python package and command line tool for fetching and parsing Associated Press election results.

Density, distribution function, quantile function
    and random generation for the Kumaraswamy Complementary Weibull
    Geometric (Kw-CWG) lifetime probability distribution proposed
    in Afify, A.Z. et al (2017) <doi:10.1214/16-BJPS322>.

Performs hypothesis testing for general block designs with
    empirical likelihood. The core computational routines are implemented
    using the 'Eigen' 'C++' library and 'RcppEigen' interface, with
    'OpenMP' for parallel computation. Details of the methods are given in
    Kim, MacEachern, and Peruggia (2023)
    <doi:10.1080/10485252.2023.2206919>. This work was supported by the
    U.S. National Science Foundation under Grants No.  SES-1921523 and
    DMS-2015552.

A tool to draw samples from a Empirical Likelihood Bayesian posterior
   of parameters using Hamiltonian Monte Carlo.

To run data analysis for enzyme-link immunosorbent assays (ELISAs). 
	Either the five- or four-parameter logistic model will be fitted for data of single ELISA. 
	Moreover, the batch effect correction/normalization will be carried out, when there are more than one batches of ELISAs. 
	Feng (2018) <doi:10.1101/483800>.

An alternative to Exploratory Factor Analysis (EFA) for
    metrical data in R. Drawing on characteristics of classical test
    theory, Exploratory Likert Scaling (ELiS) supports the user exploring
    multiple one-dimensional data structures. In common research practice,
    however, EFA remains the go-to method to uncover the (underlying)
    structure of a data set. Orthogonal dimensions and the potential of
    overextraction are often accepted as side effects. As described in
    Müller-Schneider (2001) <doi:10.1515/zfsoz-2001-0404>), ELiS confronts
    these problems. As a result, 'elisr' provides the platform to fully
    exploit the exploratory potential of the multiple scaling approach
    itself.