data(p12.12)
attach(p12.12)
# fitting the linearized model
logy.lm <- lm(I(log(y))~I(log(x1))+I(log(x2)))
summary(logy.lm)
plot(logy.lm, which=1) # checking the residuals
# fitting the nonlinear model
y.nls <- nls(y ~ theta1*I(x1^theta2)*I(x2^theta3), start=list(theta1=.95,
theta2=.76, theta3=.21))
summary(y.nls)
plot(resid(y.nls)~fitted(y.nls)) # checking the residuals
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