R/RcppExports.R

In sergioventurini/SAuR: Sensitivity Analysis Using R

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#' Moving average data smoother.
#'
#' Computation of a moving average data smoother.
#'
#' @param x A numeric vector containing the data to analyze.
#' @param p A length-one numeric vector.
#' @return A \code{matrix} object.
#' @author Sergio Venturini \email{sergio.venturini@unito.it}
#' @seealso \code{\link{betaKS3_R}} for computing the sensitivity measures.
#' @references
#'   Venturini, S., Borgonovo, E. (2020), "Sensitivity Analysis Using 
#'   \code{R}: the \pkg{SAuR} Package", Technical report.
#' @examples
#' \dontrun{
#' data(simdata_sub, package = "SAuR")
#'
#' }
#'
#' @export
mollify_rcpp <- function(x, p) {
    .Call('_SAuR_mollify_rcpp', PACKAGE = 'SAuR', x, p)
}

#' Discrete Cosine Transform.
#'
#' Returns the (normalized) discrete cosine transform of a sequence of
#'  numbers (see \url{https://www.mathworks.com/help/signal/ref/dct.html}).
#'
#' @param x A numeric vector containing the data to analyze.
#' @param norm A length-one logical vector specifying whether to normalize the
#'   result or not
#' @return A numeric vector containing the discrete cosine transform.
#' @author Sergio Venturini \email{sergio.venturini@unito.it}
#' @seealso \code{\link{dct_fft}} and \code{\link{cosi}} for computing the
#'   conditional regression line.
#' @references
#'   Venturini, S., Borgonovo, E. (2020), "Sensitivity Analysis Using 
#'   \code{R}: the \pkg{SAuR} Package", Technical report.
#' @examples
#' \dontrun{
#' data(simdata_sub, package = "SAuR")
#'
#' }
#'
#' @aliases dct_rcpp
#'
#' @export
dct_rcpp <- function(x, norm) {
    .Call('_SAuR_dct_rcpp', PACKAGE = 'SAuR', x, norm)
}

#' Discrete Cosine Transform.
#'
#' Returns the (normalized) discrete cosine transform of a sequence of
#'  numbers (see \url{https://www.mathworks.com/help/signal/ref/dct.html}).
#'
#' @param x A numeric vector containing the data to analyze.
#' @param norm A length-one logical vector specifying whether to normalize the
#'   result or not
#' @return A numeric vector containing the discrete cosine transform.
#' @author Sergio Venturini \email{sergio.venturini@unito.it}
#' @seealso \code{\link{cosi}} for computing the conditional regression line.
#' @references
#'   Venturini, S., Borgonovo, E. (2020), "Sensitivity Analysis Using 
#'   \code{R}: the \pkg{SAuR} Package", Technical report.
#' @examples
#' \dontrun{
#' data(simdata_sub, package = "SAuR")
#'
#' }
#'
#' @aliases dct_fft
#'
#' @export
dct_fft <- function(x, norm) {
    .Call('_SAuR_dct_fft', PACKAGE = 'SAuR', x, norm)
}

#' Discrete Cosine Transform.
#'
#' Returns the (normalized) discrete cosine transform of a sequence of
#'  numbers (see \url{https://www.mathworks.com/help/signal/ref/dct.html}).
#'
#' @param x A numeric vector containing the data to analyze.
#' @param norm A length-one logical vector specifying whether to normalize the
#'   result or not
#' @return A numeric vector containing the discrete cosine transform.
#' @author Sergio Venturini \email{sergio.venturini@unito.it}
#' @seealso \code{\link{dct_fft}} and \code{\link{cosi}} for computing the
#'   conditional regression line.
#' @references
#'   Venturini, S., Borgonovo, E. (2020), "Sensitivity Analysis Using 
#'   \code{R}: the \pkg{SAuR} Package", Technical report.
#' @examples
#' \dontrun{
#' data(simdata_sub, package = "SAuR")
#'
#' }
#'
#' @aliases dct_def
#'
#' @export
dct_def <- function(x, norm) {
    .Call('_SAuR_dct_def', PACKAGE = 'SAuR', x, norm)
}

#' Inverse Discrete Cosine Transform.
#'
#' Returns the (normalized) inverse discrete cosine transform of a sequence of
#'  numbers (see \url{https://www.mathworks.com/help/signal/ref/idct.html}).
#'
#' @param x A numeric vector containing the data to analyze.
#' @param norm A length-one logical vector specifying whether to normalize the
#'   result or not
#' @return A numeric vector containing the inverse discrete cosine transform.
#' @author Sergio Venturini \email{sergio.venturini@unito.it}
#' @seealso \code{\link{idct_fft}} and \code{\link{cosi}} for computing the
#'   conditional regression line.
#' @references
#'   Venturini, S., Borgonovo, E. (2020), "Sensitivity Analysis Using 
#'   \code{R}: the \pkg{SAuR} Package", Technical report.
#' @examples
#' \dontrun{
#' data(simdata_sub, package = "SAuR")
#'
#' }
#'
#' @aliases idct_def
#'
#' @export
idct_def <- function(x, norm) {
    .Call('_SAuR_idct_def', PACKAGE = 'SAuR', x, norm)
}

#' Inverse Discrete Cosine Transform.
#'
#' Returns the (normalized) inverse discrete cosine transform of a sequence of
#'  numbers (see \url{https://www.mathworks.com/help/signal/ref/idct.html}).
#'
#' @param x A numeric vector containing the data to analyze.
#' @param norm A length-one logical vector specifying whether to normalize the
#'   result or not
#' @return A numeric vector containing the inverse discrete cosine transform.
#' @author Sergio Venturini \email{sergio.venturini@unito.it}
#' @seealso \code{\link{cosi}} for computing the conditional regression line.
#' @references
#'   Venturini, S., Borgonovo, E. (2020), "Sensitivity Analysis Using 
#'   \code{R}: the \pkg{SAuR} Package", Technical report.
#' @examples
#' \dontrun{
#' data(simdata_sub, package = "SAuR")
#'
#' }
#'
#' @aliases idct_fft
#'
#' @export
idct_fft <- function(x, norm) {
    .Call('_SAuR_idct_fft', PACKAGE = 'SAuR', x, norm)
}