investr: An R Package for Inverse Estimation

Inverse estimation is a classical and well-known problem in regression. In simple terms, it involves the use of an observed value of the response to make inference on the corresponding unknown value of the explanatory variable. To our knowledge, however, statistical software is somewhat lacking the capabilities for analyzing these types of problems. In this paper1 , we introduce investr (which stands for inverse estimation in R), a package for solving inverse estimation problems in both linear and nonlinear regression models.

Brandon M. Greenwell , Christine M. Schubert Kabban

CRAN packages used

investr, MASS, drc, car, boot

CRAN Task Views implied by cited packages

Econometrics, SocialSciences, ChemPhys, Multivariate, Pharmacokinetics, Distributions, Environmetrics, Finance, NumericalMathematics, Optimization, Psychometrics, Robust, Survival, TimeSeries


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For attribution, please cite this work as

Greenwell & Kabban, "The R Journal: investr: An R Package for Inverse Estimation", The R Journal, 2014

BibTeX citation

  author = {Greenwell, Brandon M. and Kabban, Christine M. Schubert},
  title = {The R Journal: investr: An R Package for Inverse Estimation},
  journal = {The R Journal},
  year = {2014},
  note = {},
  doi = {10.32614/RJ-2014-009},
  volume = {6},
  issue = {1},
  issn = {2073-4859},
  pages = {90-100}