R/Y_ex_5_1.R

In BNPMIXcluster: Bayesian Nonparametric Model for Clustering with Mixed Scale Variables

#'
#' @docType data
#'
#' @name
#'     Y_ex_5_1
#'
#' @title
#'     Simulated data for testing the \emph{BNPMIXcluster} package
#'
#' @description
#' 
#'     List with three data frames. Each dataset consists of the data \eqn{Y_i} described in the exercise of section 5.1 in the article Carmona et al (2017).
#'
#'     The data \code{Y_ex_5_1} is a transformation of the simulated data \code{Z_latent_ex_5_1}.
#'
#'
#' @usage
#'     Y_ex_5_1
#'
#' @format
#'     A list with three data frames.
#'
#' @details
#'     A list with three data frames. Each data frame with 100 rows.
#'
#' @examples
#'
#' ### Show the relation between Y_ex_5_1 and Z_latent_ex_5_1 ###
#' 
#' plot(y=Y_ex_5_1[[3]][,"Y1"],x=Z_latent_ex_5_1$Z1,pch=20,col=2); abline(v=c(5),lty=3)
#' plot(y=Y_ex_5_1[[3]][,"Y2"],x=Z_latent_ex_5_1$Z2,pch=20,col=2); abline(v=c(5),lty=3)
#' plot(y=Y_ex_5_1[[3]][,"Y3"],x=Z_latent_ex_5_1$Z3,pch=20,col=2); abline(v=c(5),lty=3)
#'
#'   
#' ##############################
#' #        Exercise 5.1        #
#' #      Data definition       #
#' ##############################
#'
#' ### Code to generate Y_ex_5_1 from Z_latent_ex_5_1 ###
#' 
#' Y_ex_5_1 <- list()
#' 
#' ## (I) ##
#' # Three continuous variables (Y1, Y2, Y3)
#' # defined as Yi = Zi, for i=1, 2, 3.
#' Y_ex_5_1[[1]] <- Z_latent_ex_5_1[,c("Z1","Z2","Z3")]
#' 
#' ## (II) ##
#' # two binary variables (Y1 , Y3 ) defined as
#' # Y1 = I(Z1 > 5)
#' # Y3 = I(Z3 > 3)
#' Y_ex_5_1_i <- data.frame(matrix(NA,nrow=nrow(Z_latent_ex_5_1),ncol=2))
#' colnames(Y_ex_5_1_i) <- paste("Y",c(1,3),sep="")
#' Y_ex_5_1_i$Y1 <- findInterval( Z_latent_ex_5_1$Z1, c(-Inf,5,Inf) )-1
#' Y_ex_5_1_i$Y3 <- findInterval( Z_latent_ex_5_1$Z3, c(-Inf,3,Inf) )-1
#' Y_ex_5_1[[2]] <- Y_ex_5_1_i
#' 
#' ## (III) ##
#' # two binary variables (Y1 , Y3 ) defined as in Scenario (II)
#' # one ordinal variable Y2 such that Y2 = I(4 < Z2 < 5) + 2 * I(z 2 > 5)
#' # and one continuous variable Y4 distributed N(0, 1)
#' Y_ex_5_1_i <- data.frame(matrix(NA,nrow=nrow(Z_latent_ex_5_1),ncol=4))
#' colnames(Y_ex_5_1_i) <- paste("Y",1:4,sep="")
#' Y_ex_5_1_i$Y1 <- Y_ex_5_1[[2]]$Y1
#' Y_ex_5_1_i$Y2 <- findInterval( Z_latent_ex_5_1$Z2, c(-Inf,4,5,Inf) )-1
#' Y_ex_5_1_i$Y3 <- Y_ex_5_1[[2]]$Y3
#' Y_ex_5_1_i$Y4 <- rnorm(n=nrow(Z_latent_ex_5_1),mean=0,sd=1)
#' Y_ex_5_1[[3]] <- Y_ex_5_1_i
#' 
#' 
#' Y_ex_5_1
#' 
#' 
#' @seealso
#' \code{\link{MIXclustering}}
#'

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