670
Le logiciel R
12.5- modele.complet <- lm(chom∼txpib+deppub+pfisc+salva+infl,
data=chomage)
summary(modele.complet)
12.6- require("car")
vif(modele.complet)
12.7- drop1(lm(chom∼txpib+deppub+pfisc+salva+infl,data=chomage),
test="F")
# On enl` eve la variable infl.
drop1(lm(chom∼txpib+deppub+pfisc+salva,data=chomage),test="F")
# On enl` eve la variable txpib.
drop1(lm(chom∼deppub+pfisc+salva,data=chomage),test="F")
# On enl` eve la variable pfisc.
drop1(lm(chom∼deppub+salva,data=chomage),test="F")
12.8- # Mod` ele final:
modele.final <- lm(chom∼deppub+salva,data=chomage)
summary(modele.final)
12.9- deppub93 <- chomage$deppub[chomage$an==1993]
salva93 <- chomage$salva[chomage$an==1993]
predict(modele.final,data.frame(deppub=deppub93,salva=salva93),
interval="prediction")
12.10- La valeur observ´ ee de chom en 1993 ´ etait de 11.2 et cette valeur est contenue dans l’intervalle de pr´ evision.
C- ´
Etude sur la r´ egression polynomiale
• ´
Etude sur donn´ ees simul´ ees
12.1- n <- 100
x <- runif(n,min=-2,max=2)
eps <- rnorm(n)
y <- x+2 * (x^2)+3.5 * (x^3)-2.3 * (x^4)+eps
12.2- plot(y∼x)
curve(x+2 * x * x+3.5 * x^3-2.3 * x^4,add=TRUE)
12.3- modele.simple <- lm(y∼x)
summary(modele.simple)
hist(residuals(modele.simple))
plot(modele.simple,1:6)