Calibration Functions

#' 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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