# Y_ex_5_1: Simulated data for testing the _BNPMIXcluster_ package In BNPMIXcluster: Bayesian Nonparametric Model for Clustering with Mixed Scale Variables

## Description

List with three data frames. Each dataset consists of the data Y_i described in the exercise of section 5.1 in the article Carmona et al (2017).

The data `Y_ex_5_1` is a transformation of the simulated data `Z_latent_ex_5_1`.

## Usage

 `1` ```Y_ex_5_1 ```

## Format

A list with three data frames.

## Details

A list with three data frames. Each data frame with 100 rows.

`MIXclustering`
 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45``` ```### 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 ```