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+#' @title SyncRNG - Synchronized Random Numbers in R and Python
+#' 
+#' @description 
+#' The SyncRNG package provides a random number generator implemented in C and 
+#' linked to both R and Python. This way, you can generate the same random 
+#' number sequence in both languages by using the same seed.
+#'
+#' The package implements a Tausworthe LSFR RNG (more details at 
+#' \url{https://gertjanvandenburg.com/blog/syncrng/}). This is a very fast 
+#' pseudo-random number generator.
+#'
+#' @section Usage:
+#' There are two ways to use this package in R. It can be used as a reference 
+#' class, where a SyncRNG object is used to keep the state of the generator and 
+#' numbers are generated using the object methods. It can also be used as a 
+#' user-defined random number generator using the strategy outlined in 
+#' .Random.user. See the examples section below.
+#'
+#' @author
+#' Gerrit J.J. van den Burg\cr
+#' Maintainer: Gerrit J.J. van den Burg <gertjanvandenburg@gmail.com>
+#'
+#' @references
+#' URL: \url{https://github.com/GjjvdBurg/SyncRNG}
+#'
+#' @examples
+#' library(SyncRNG)
+#'
+#' # As user defined RNG:
+#'
+#' set.seed(0, 'user', 'user')
+#' runif(2)
+#' # [1] 3.666952e-04 6.257184e-05
+#' set.seed(0, 'user', 'user')
+#' rnorm(2)
+#' # [1] 0.01006027 0.42889422
+#'
+#' # As class:
+#'
+#' s <- SyncRNG(seed=0)
+#' s$rand()
+#' # [1] 0.0003666952
+#' s$rand()
+#' # [1] 6.257184e-05
+#'
+#' @name syncrng-package
+#' @docType package
+#' @import methods
+NULL
+#>NULL