#' Transform to Uniform Scale
#'
#'
#' Transform a vector with support on [a, b] to have
#' support on [0, 1].
#' @param x A vector of values.
#' @export
uniformize = function(x, a = NA, b = NA){
if (is.na(a)){
a = min(x, na.rm = TRUE)
}
if (is.na(b)){
b = min(x, na.rm = TRUE)
}
x.transformed = (x - a)/(b - a)
return(x.transformed)
}
#' Gaussian Kernel of Scalar
#'
#' Returns the standard Gaussian kernel evaluated at u.
#' @param u Evaluation points
#' @keywords kernel
#' @export
gaussian.kernel = function(u){
return(exp(-u^2/2)/sqrt(2*pi))
}
#' Embed a Scalar Time Series
#'
#' Embeds a scalar time series in a regression-like matrix.
#' @param ts The scalar time series.
#' @param L The block length used to embed.
#' @keywords time series, embedding, regression
#' @export
embed.ts = function(ts, L = 2){
n = length(ts)
ts.embedded = matrix(0, nrow = n - (L - 1), ncol = L)
for (start.ind in 1:L){
ts.embedded[, start.ind] = ts[((start.ind-1) + 1):(n - (L - 1) + (start.ind-1))]
}
return(ts.embedded)
}
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.