Example of a quadratic model fit in R

parabola_fit.R

#-------------------------------------------------------------------------------
#                          Parabola y = a + bx + cx^2
#-------------------------------------------------------------------------------

model2 <- lm(wt ~ disp+I(disp^2))
summary(model2)
coef(model2)

# Predicted vs original
predicted <- fitted(model2)
original <- wt

# Plot model2
curve(predict(model2,data.frame(disp=x)),col='green',lwd=2,add=TRUE)

#-------------------------------------------------------------------------------
#                       Polynomial n=3 y = a +bx + cx^2 + dx^3
#-------------------------------------------------------------------------------

model3 <- lm(wt ~ disp+ I(disp^2) + I(disp^3))
summary(model3)
coef(model3)

# Predicted vs original
predicted <- fitted(model3)
original <- wt

# Plot model3
curve(predict(model3,data.frame(disp=x)),col='blue',lwd=2,add=TRUE)

from the above example how to perform a lack of fit test?