Actually this converges very nicely if you use these starting values
that I obtained with
AD Model Builder
th 9.1180e-01
b0 5.2104e+00
b1 -4.6725e-04
The R result looks like
nls.m2
Nonlinear regression model
model: Retention ~ expFct(Area, b0, b1, th)
data: structure(list(Area = c(521.5, 689.78, 1284.71, 2018.8,
2560.46, 524.91, 989.05, 1646.32, 2239.65, 2972.96, 478.54, 875.52,
1432.5, 2144.74, 2629.2), Retention = c(95.3, 87.18, 44.94, 26.36,
18.12, 84.68, 37.24, 33.04, 23.46, 9.72, 97.92, 71.44, 44.52, 24.44,
15.26)), .Names = c("Area", "Retention"), row.names = c(NA, -15L), class
= "data.frame")
b0 b1 th
5.2104466 -0.0004672 0.9118029
residual sum-of-squares: 686.8
Number of iterations to convergence: 1
Achieved convergence tolerance: 1.75e-06
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