Implements the RecMap MP2 construction heuristic
  <doi:10.1109/INFVIS.2004.57>.
  This algorithm draws maps according to a given statistical
  value, e.g., election results, population, or epidemiological data.
  The basic idea of the RecMap algorithm is that each map region,
  e.g., different countries, is represented by a rectangle.
  The area of each rectangle represents the statistical value given
  as input (maintain zero cartographic error).
  C++ is used to implement the computationally intensive tasks.
  The vignette included in this package provides documentation
  about the usage of the recmap algorithm.

Modern results of psychometric theory are implemented to provide users with a way of evaluating the internal structure of a set of items guided by theory. These methods are discussed in detail in VanderWeele and Padgett (2024) <doi:10.31234/osf.io/rnbk5>. The relative excess correlation matrices will, generally, have numerous negative entries even if all of the raw correlations between each pair of indicators are positive. The positive deviations of the relative excess correlation matrix entries help identify clusters of indicators that are more strongly related to one another, providing insights somewhat analogous to factor analysis, but without the need for rotations or decisions concerning the number of factors. A goal similar to exploratory/confirmatory factor analysis, but 'recmetrics' uses novel methods that do not rely on assumptions of latent variables or latent variable structures.

The ecocrop model estimates environmental suitability for plants using a limiting factor approach for plant growth following Hackett (1991) <doi:10.1007/BF00045728>. The implementation in this package is fast and flexible: it allows for the use of any (environmental) predictor variable. Predictors can be either static (for example, soil pH) or dynamic (for example, monthly precipitation).

Contains functions to interface with variables and variable details sheets, including recoding variables and converting them to PMML.