I am using LOF.test() function from the qpcR package and got the following
result:
> LOF.test(nlregmod3)
$pF
[1] 0.97686
$pLR
[1] 0.77025
Can I conclude from the LOF.test() results that my nonlinear regression
model is significant/statistically significant?
Where my nonlinear model was fitted as follows:
nlregmod3 <- nlsr(formula=y ~ theta1 - theta2*exp(-theta3*x), data =
mod14data2_random,
start = list(theta1 = 0.37,
theta2 = -exp(-1.8),
theta3 = 0.05538))
And the data used to fit this model is the following:
dput(mod14data2_random)
structure(list(index = c(14L, 27L, 37L, 33L, 34L, 16L, 7L, 1L,
39L, 36L, 40L, 19L, 28L, 38L, 32L), y = c(0.44, 0.4, 0.4, 0.4,
0.4, 0.43, 0.46, 0.49, 0.41, 0.41, 0.38, 0.42, 0.41, 0.4, 0.4
), x = c(16, 24, 32, 30, 30, 16, 12, 8, 36, 32, 36, 20, 26, 34,
28)), row.names = c(NA, -15L), class = "data.frame")
Cheers,
Paul
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