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.

Addons for the 'mice' package to perform multiple imputation using chained equations with two-level data. Includes imputation methods dedicated to sporadically and systematically missing values. Imputation of continuous, binary or count variables are available. Following the recommendations of Audigier, V. et al (2018) <doi:10.1214/18-STS646>, the choice of the imputation method for each variable can be facilitated by a default choice tuned according to the structure of the incomplete dataset. Allows parallel calculation and overimputation for 'mice'.

Multiple Imputation has been shown to 
  be a flexible method to impute missing values by 
  Van Buuren (2007) <doi:10.1177/0962280206074463>. 
  Expanding on this, random forests have been shown 
  to be an accurate model by Stekhoven and Buhlmann 
  <arXiv:1105.0828> to impute missing values in datasets. 
  They have the added benefits of returning out of bag 
  error and variable importance estimates, as well as 
  being simple to run in parallel.