R/data.R

In weiyaw/blackbox: A SMC-SA Algorithm for Constrained Optimisation

#' Data from a hyperbolic tangent function.
#'
#' A simulated dataset from a hyperbolic tangent function y = 1 + tanh(x - 3) + eps, where 'eps' is a Gaussian noise with 0 mean and 0.3 standard deviation.
#'
#' @format A data frame with 30 rows and 2 columns (x and y).
#' \describe{
#'   \item{x}{30 equidistant numbers from 0 to 6.}
#'   \item{y}{responses corresponds to each x.}
#' }
"hyper"

#' Data from a hyperbolic tangent function with two outliers.
#'
#' A simulated dataset from a hyperbolic tangent function y = 1 + tanh(x - 3) + eps, where 'eps' is a Gaussian noise with 0 mean and 0.3 standard deviation. This dataset is corrupted with two outliers (2nd and 29th rows).
#'
#' @format A data frame with 30 rows and 2 columns (x and y).
#' \describe{
#'   \item{x}{30 equidistant numbers from 0 to 6.}
#'   \item{y}{responses corresponds to each x.}
#' }
"hyper_out"