#'
#' @param mr Output of multiRun(), list of lists of functions results
#' @param x Row index of the element inside the aggregated parameter
-#' @param y Colomn index of the element inside the aggregated parameter
+#' @param y Column index of the element inside the aggregated parameter
#'
#' @examples
-#' \dontrun{
+#' \donttest{
#' β <- matrix(c(1,-2,3,1),ncol=2)
#' mr <- multiRun(...) #see bootstrap example in ?multiRun : return lists of mu_hat
#' μ <- normalize(β)
avg_param <- as.double(params_hat[[i]])
std_param <- as.double(stdev[[i]])
matplot(cbind(params[o],avg_param[o],avg_param[o]+std_param[o],avg_param[o]-std_param[o]),
- col=c(2,1,1,1), lty=c(1,1,2,2), type="l", lwd=2, xlab="param", ylab="value")
+ col=1, lty=c(1,5,2,2), type="l", lwd=2, xlab="param", ylab="value")
}
#print(o) #not returning o to avoid weird Jupyter issue... (TODO:)
#' Draw 3D map of objective function values
#'
#' @param N Number of starting points
+#' @param n Number of points in sample
+#' @param p Vector of proportions
+#' @param b Vector of biases
#' @param β Regression matrix (target)
#' @param link Link function (logit or probit)
#'