I have the following data set, and I have to find the line of best fit using
this equation,
y = a*(1 - exp(-b*x)).
samples = seq(1,20,by=1)
species = c(5,8,9,9,11,11,12,15,17,19,20,20,21,23,23,25,25,27,27,27)
plot(samples,species, main = Accumulation Curve for Tree Species Richness,
xlab =
Hi,
Try
d - data.frame(samples, species)
fit = nls(species ~ a *(1 - exp(-b*samples)), start = list(a = 27, b =
.15), data = d)
summary(fit)
Formula: species ~ a * (1 - exp(-b * samples))
Parameters:
Estimate Std. Error t value Pr(|t|)
a 35.824723.02073 11.860 6.10e-10 ***
b 0.07168
I think that you probably need to provide the x values to nls. Try,
for example,
fit - nls(species ~ a *(1 - exp(-b*samples)),start = list(a = 27, b = .15))
I hope that this helps,
Andrew
On Thu, Apr 28, 2011 at 01:56:43PM -0700, BornSurvivor wrote:
I have the following data set, and I have
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