Functions to create normally distributed data between two values minimum and maximum. One function pegs the minimum and maximum; the other uses a 99.7% tolerance interval.

rnorm.r

#' @title Returns a normally distributed vector within the 99.7% tolerance interval defined by minimum and maximum
#' @param n (required) The number of random numbers to generate
#' @param minimum (optional) The lower 99.9% tolerance limit
#' @param maximum (optional) The upper 99.9% tolerance limit
#' @return numeric vector with n elements randomly distributed so that approximately 99.7% of values will fall between minimum and maximum
#' @examples
#'  rnorm.within(10)
#'  rnorm.within(10, 10, 20)
#'  summary(rnorm.within(10000, 10, 20))
rnorm.within <- function(n, minimum=0, maximum=1)
{
  x <- rnorm(n, mean = 0, sd = 1)
  x <- x - -3
  x <- x / (6)
  x <- x * (maximum - minimum)
  x <- x + minimum
  
  return(x)
}

#' @title Returns a normally distributed vector between minimum and maximum
#' @param n (required) The number of random numbers to generate
#' @param minimum (optional) The minimum value to return
#' @param maximum (optional) The maximum value to return
#' @return numeric vector with n elements randomly distributed between minimum and maximum
#' @examples
#'  rnorm.between(10)
#'  rnorm.between(10, 10, 20)
#'  summary(rnorm.between(10000, 10, 20))
rnorm.between <- function(n, minimum = 0, maximum = 1)
{
  x <- rnorm(n)
  max_x <- max(x)
  min_x <- min(x)
  x <- x - min_x
  x <- x / (max_x - min_x)
  x <- x * (maximum - minimum)
  x <- x + minimum
  
  return(x)
}