Various tools for microeconomic analysis and microeconomic modelling,
   e.g. estimating quadratic, Cobb-Douglas and Translog functions,
   calculating partial derivatives and elasticities of these functions,
   and calculating Hessian matrices, checking curvature
   and preparing restrictions for imposing monotonicity of Translog functions.

Functions and tools
   for analysing consumer demand
   with the Almost Ideal Demand System (AIDS)
   suggested by Deaton and Muellbauer (1980).

Tools for econometric analysis and economic modelling
   with the traditional two-input Constant Elasticity of Substitution (CES) function
   and with nested CES functions with three and four inputs.
   The econometric estimation can be done by the Kmenta approximation,
   or non-linear least-squares
   using various gradient-based or global optimisation algorithms.
   Some of these algorithms can constrain the parameters to certain ranges,
   e.g. economically meaningful values.
   Furthermore, the non-linear least-squares estimation
   can be combined with a grid-search for the rho-parameter(s).
   The estimation methods are described in Henningsen et al. (2021)
   <doi:10.4337/9781788976480.00030>.

Econometric analysis of multiple-input-multiple-output
  production technologies with ray-based input distance functions as suggested
  by Price and Henningsen (2022): "A Ray-Based Input Distance Function to Model
  Zero-Valued Output Quantities: Derivation and an Empirical Application",
  <https://ideas.repec.org/p/foi/wpaper/2022_03.html>.

Tools for calculating Laspeyres, Paasche, and Fisher
  price and quantity indices.

Tools for econometric production analysis
   with the Symmetric Normalized Quadratic (SNQ) profit function,
   e.g. estimation, imposing convexity in prices,
   and calculating elasticities and shadow prices.

Fast imputations under the object-oriented programming paradigm. 	
  Moreover there are offered a few functions built to work with popular R packages such as 'data.table' or 'dplyr'.
  The biggest improvement in time performance could be achieve for a calculation where a grouping variable have to be used.
  A single evaluation of a quantitative model for the multiple imputations is another major enhancement.
  A new major improvement is one of the fastest predictive mean matching in the R world because of presorting and binary search.