R/Data_saekernel.R

In saekernel: Small Area Estimation Non-Parametric Based Nadaraya-Watson Kernel

#' @title Sample Data for Small Area Estimation Non-Parametric Based Nadaraya-Watson Kernel
#'
#' @description Dataset to Simulate Small Area Estimation Non-Parametric Based Nadaraya-Watson Kernel
#'
#' This data is generated by these following steps:
#'   \enumerate{
#'     \item Generate explanatory variables \code{Vardir}. \code{Vardir ~ abs(N(0, 0.1))}
#'     \cr Generate explanatory variables \code{x}. \code{x ~ U(min=0, max=1)}
#'     \cr Calculate direct estimation \code{y} where \eqn{y_{i}}{yi} = \eqn{sin(2 * \pi * x^3) + 5}
#'     \item Then combine the direct estimations \code{y}, auxiliary variables \code{x}, and sampling varians \code{Vardir} in a dataframe then named as Data_saekernel
#'   }
#'
#' @format A data frame with 100 rows and 3 variables:
#' \describe{
#'   \item{y}{Direct Estimation of Y}
#'   \item{x}{Auxiliary Variable of X}
#'   \item{Vardir}{Sampling Variance of Y}
#' }
#'
"Data_saekernel"