A collection of advanced tools, methods and models specifically  designed  for  analyzing different  types  of  ecological  networks - especially  antagonistic  (food  webs,  host-parasite),  mutualistic (plant-pollinator, plant-fungus, etc)  and competitive networks, as well as their variability in time and space. Statistical models are developed to describe and understand the mechanisms that determine species interactions, and to decipher the organization of these ecological networks (Ohlmann et al. (2019)  <doi:10.1111/ele.13221>, Gonzalez et al. (2020) <doi:10.1101/2020.04.02.021691>, Miele et al. (2021) <doi:10.48550/arXiv.2103.10433>, Botella et al (2021) <doi:10.1111/2041-210X.13738>).

Computes a series of indices commonly used in the fields of economic geography, economic complexity, and evolutionary economics to describe the location, distribution, spatial organization, structure, and complexity of economic activities. Functions include basic spatial indicators such as the location quotient, the Krugman specialization index, the Herfindahl or the Shannon entropy indices but also more advanced functions to compute different forms of normalized relatedness between economic activities or network-based measures of economic complexity. Most of the functions use matrix calculus and are based on bipartite (incidence) matrices consisting of region - industry pairs. These are described in Balland (2017) <http://econ.geo.uu.nl/peeg/peeg1709.pdf>.

Provides utility functions for standardizing economic entity 
  (economy, aggregate, institution, etc.) name and id in economic datasets such 
  as those published by the International Monetary Fund and World Bank. Aims to 
  facilitate consistent data analysis, reporting, and joining across datasets. 
  Used as a foundational building block in the 'EconDataverse' family of 
  packages (<https://www.econdataverse.org>).

A wrapper of different methods from Linear Algebra for the equations
  introduced in The Atlas of Economic Complexity and related literature. This
  package provides standard matrix and graph output that can be used seamlessly
  with other packages. See <doi:10.21105/joss.01866> for a summary
  of these methods and its evolution in literature.