Hello,

I want to understand how to tell if a model is significant.

For example I have vectX1 and vectY1.
I seek first what model is best suited for my vectors and
then I want to know if my result is significant.

I'am doing like this:

model1 <- lm(vectY1 ~ vectX1, data= d),

model2 <- nls(vectY1 ~ a*(1-exp(-vectX1/b)) + c, data= d,
start = list(a=1, b=3, c=0))

aic1 <- AIC(model1)
aic2 <- AIC(model2)

if (aic1 < aic2) print("Model1 is better")
else print("Model2 is better")

for example aic1 < aic2 I'am doing summary(model1) and I have p-value to
know if my result is significant.

but if  aic2 < aic1, so model 2, non linear is better. I'am doing
summary(model2) bur there isn't p-value. I read that it is normal. So how
can I know if my resultat is significant?

I can't use summary.nls(), because, I'm working with mac and it's no
possible to install it.


Thank you

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