redo documentation, bump version, use https urls

DESCRIPTION

@@ -1,12 +1,12 @@
 Package: learNN
 Title: Examples of Neural Networks
-Version: 0.2.0.9000
+Version: 0.5.0
 Authors@R: person("Bastiaan", "Quast", email = "bquast@gmail.com", role = c("aut", "cre"))
 Description: Implementations of several basic neural network concepts in R, as
-    based on posts on \url{http://qua.st/}.
+    based on posts on \url{https://qua.st/}.
 Depends:
-    R (>= 2.10.0)
+    R (>= 3.6.0)
 License: GPL-3
 Suggests:
     testthat
-RoxygenNote: 5.0.0
+RoxygenNote: 7.0.2

R/learNN.R

@@ -4,5 +4,5 @@
 #' Bastiaan Quast \email{bquast@@gmail.com}
 #' @title Learn Neural Networks
 #' @description Implementations of several basic neural network concepts in R,
-#' as based on posts on \url{http://qua.st/}.
+#' as based on posts on \url{https://qua.st/}.
 NULL

R/learn_bp.R

@@ -4,8 +4,8 @@
 #' @param X input data
 #' @param y output data
 #' @importFrom stats runif
-#' @references \url{http://qua.st/handcoding-neural-network/}
-#' \url{http://iamtrask.github.io/2015/07/12/basic-python-network/}
+#' @references \url{https://qua.st/handcoding-neural-network/}
+#' \url{https://iamtrask.github.io/2015/07/12/basic-python-network/}
 #' @export
 #' @examples
 #' # create data

R/learn_do.R

@@ -9,8 +9,8 @@
 #' @importFrom stats rbinom
 #' @importFrom stats runif
 #' @export
-#' @references \url{http://qua.st/handcoding-dropout/}
-#' \url{http://iamtrask.github.io/2015/07/28/dropout/}
+#' @references \url{https://qua.st/handcoding-dropout/}
+#' \url{https://iamtrask.github.io/2015/07/28/dropout/}
 #' @examples
 #' # construct data
 #' X = matrix(c(0,0,1,0,1,1,1,0,1,1,1,1), nrow=4, byrow=TRUE)

R/learn_gd.R

@@ -6,8 +6,8 @@
 #' @param hiddenSize size of the hidden layer
 #' @importFrom stats runif
 #' @export
-#' @references \url{http://qua.st/handcoding-gradient-descent/}
-#' \url{http://iamtrask.github.io/2015/07/27/python-network-part2/}
+#' @references \url{https://qua.st/handcoding-gradient-descent/}
+#' \url{https://iamtrask.github.io/2015/07/27/python-network-part2/}
 #' @examples
 #' # input dataset
 #' X = matrix(c(0,0,1,