R/iOLS_path_plot.R

In IOLS: Iterated Ordinary Least Squares Regression

#' @title iOLS_path_plot
#'
#' @description Function that plots an \code{iOLS_path} fitted model object.
#'
#' @param m An \code{iOLS_path} fitted model object.
#' @param delta_rank Among all the hyper-parameters delta,
#' we can choose to plot the "iOLS_path" fitted model object
#' corresponding to the chosen delta_rank. If a value is not precised,
#' the default value is NULL and the function will only display
#' the estimated parameter(s) in function of log(delta).
#' @param plot_beta If you want to see the trajectory
#' of one estimated parameter beta only,
#' just precise plot_beta = k (k=0 if you want to see
#' the intercept's trajectory for example). Otherwise,
#' write plot_beta = "" (the default value),
#' and you will see all parameters' trajectory.
#' In this case, the colors of each curve is assigned randomly,
#' but by precising which parameters' trajectory you want to see,
#' it will be drawn in black.
#' @param ... other parameters.
#'
#' @return a plot of an \code{iOLS_path} fitted model object.
#'
#' @examples
#' data(DATASET)
#' y = DATASET$y
#' x = as.matrix(DATASET[,c("X1","X2")])
#' lm = lm(log(y+1) ~ x)
#' lm_coef = c(coef(lm))
#' X = cbind(rep(1, nrow(x)), x)
#' k = iOLS_path(y, X, b_init = lm_coef, deltainf = 10^-5,
#' deltasup = 10^4, nbre_delta = 20,
#' epsi = 10^-3, error_type = "HC0")
#'
#' #All the parameters, as a function of log(delta) (ie. each triplet from an iOLS regression) :
#' iOLS_path_plot(k)
#'
#' #All the parameters from the 6th iOLS regression :
#' iOLS_path_plot(k, delta_rank = 6)
#'
#' #Intercept from the 6th iOLS regression :
#' iOLS_path_plot(k, delta_rank = 6, plot_beta = 0)
#'
#' @export
iOLS_path_plot <- function(m, delta_rank = NULL, plot_beta = "", ...) {

  if (is.null(delta_rank)) {
    if (plot_beta == "") {
      for (i in 1:(dim(cbind(m$x))[2]+1)) {
        plot(
          m$coef_iter[, i] ~ log(m$delta_list),
          ylim = c(-5, 5),
          col = randomColor(),
          ylab = 'beta',
          xlab = 'log(delta)',
          pch = 20
        )
        oldpar <- par(no.readonly = TRUE)
        on.exit(par(oldpar))
        par(new = TRUE)
      }
    }
    else {
      plot(
        m$coef_iter[, plot_beta + 1] ~ log(m$delta_list),
        ylim = c(-5, 5),
        col = "black",
        ylab = str_c('beta', plot_beta),
        xlab = 'log(delta)',
        pch = 20
      )
    }
  }
  else {
    if (plot_beta == "") {
      iOLS_plot(m$iols[[delta_rank]])
    }
    else {
      iOLS_plot(m$iols[[delta_rank]], plot_beta)
    }
  }
}