investr: a package for inverse estimation in R


Inverse estimation, also referred to as the calibration problem, is a classical and well-known problem in regression. In simple terms, it involves the use of an observed value of the response (or specified value of the mean response) to make inference on the corresponding unknown value of the explanatory variable.


A detailed introduction to investr has been published in The R Journal: "investr: An R Package for Inverse Estimation", You can track development at To report bugs or issues, contact the main author directly or submit them to

As of right now, investr supports (univariate) inverse estimation with objects of class:

  • lm — linear models (multiple predictor variables allowed)

  • glm — generalized linear models (multiple predictor variables allowed)

  • nls — nonlinear least-squares models

  • lme — linear mixed-effects models (fit using the nlme package)