# rm(list=ls()) 
options(OutDec = ",")
#==============================================================================
# Modelo classico de regressao linear:
# y = beta0 + beta1 x + epsilon
#==============================================================================
x  <-  seq(-0.75,4,0.001)
y  <-  1 + x 

par(mfrow=c(1,1),lwd=2.0,cex.lab=1.5,cex.axis=1.5,lab=c(10,5,5),
    mar=c(0,1,0,2.5),xpd=T,cex.main=2.0)
plot(x,y,type="l",axes=F,xlab="",ylab="",ylim=c(-1,5.75),lwd=3,col="blue")
axis(1,0:4,c("",expression(x[0]),expression(x[1]),
     expression(x[2]),"x"),col="black",lwd=2,lty=1,pos=c(0,0))
axis(2,0:5,c("","",expression(paste("E(y|x=",x[0],")")),
     expression(paste("E(y|x=",x[1],")")),
     expression(paste("E(y|x=",x[2],")")),"E(y|x)"),col="black",lwd=2,
     lty=1,pos=c(0,0),las=1)
lines(rep(1,100),seq(0,3.75,length=100),lty=1)
lines(seq(0,1.8,length=100),rep(2,100),lty=2)
lines(rep(2,100),seq(0,4.75,length=100),lty=1)
lines(seq(0,2.8,length=100),rep(3,100),lty=2)
lines(rep(3,100),seq(0,5.75,length=100),lty=1)
lines(seq(0,3.8,length=100),rep(4,100),lty=2)
z   <- seq(-1.5,1.5,length=1000)
w   <- dnorm(z,0,0.5)
lines(w+1,z+2,col="red",lwd=2)
lines(w+2,z+3,col="red",lwd=2)
lines(w+3,z+4,col="red",lwd=2)
text(x=4.0,y=5.2,cex=1.5,labels=expression(paste(beta[0]+beta[1],x)))
text(x=3.9,y=3.0,cex=1.5,labels=expression(
paste(N,bgroup("(",paste(beta[0]+beta[1],x[2],",",sigma[epsilon]^2),")"))))