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#' 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 \href{https://journal.r-project.org/archive/2014/RJ-2014-009/index.html}{introduction to investr} has been published in The R Journal:
#' "investr: An R Package for Inverse Estimation." You
#' can track development at \url{https://github.com/bgreenwell/investr}. To report
#' bugs or issues, contact the main author directly or submit them to
#' \url{https://github.com/bgreenwell/investr/issues}.
#'
#' As of right now, \code{investr} supports (univariate) inverse estimation
#' with objects of class:
#' \itemize{
#' \item{\code{lm}} --- linear models (multiple predictor variables allowed)
#' \item{\code{glm}} --- generalized linear models (multiple predictor variables allowed)
#' \item{\code{nls}} --- nonlinear least-squares models
#' \item{\code{lme}} --- linear mixed-effects models (fit using the
#' \code{nlme} package)
#' }
#'
#' @docType package
#' @name investr
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