x.1<-runif(50,0,70) x.2<-runif(20,70,90) y.1<-150-1.5*x.1+rnorm(50,3,6) y.2<-400-5*x.2+rnorm(20,2,5) x<-c(x.1,x.2) y<-c(y.1,y.2)#Plot data
plot(x,y) #continuous piecewise y.2<-y.2-100 # geser y.2 ke bawah sejauh 100, untuk diskontinuitas y.discontinue<-c(y.1,y.2) plot(x,y.discontinue) #discontinuous piecewise
######################################## #Data Soal 9.4 Mendenhall & Sincich, 7th ed, hal.475 ########################################
hours<-c(1,5,10,20,30,40,45,50,60,70,80,90,100,110,120,130,140) cells<-c(2,3,4,5,4,6,8,9,10,18,16,18,20,14,12,13,9) data.growth<-data.frame(hours,cells) data.growth plot(hours,cells) y<-cells x1<-hours x2<-NA#Membuat dummy variabel x2 untuk Model 1 ##################################
x2[x1> 60] <- 1 x2[x1<= 60] <- 0 x2star<-(x1-60)*x2#Fit regresi piecewise untuk Model 1 ############################
model.1<-lm(y~x1+x2star+x2) summary(model.1)#Bandingkan dengan Model 2 ####################### #Membuat dummy variabel x2 untuk Model 2 ###################################
x2[x1> 100] <- 1 x2[x1<= 100] <- 0 x2star<-(x1-100)*x2#Fit regresi piecewise untuk Model 2 ############################
model.2<-lm(y~x1+x2star+x2) summary(model.2)
########END########
Sebelumnya: Regresi Piecewise Diskontinu
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