Hi R users
I'm trying to fit a model y=ax^b.
I know if I made ln(y)=ln(a)+bln(x) this is a linear regression.
But I obtain differente results with nls() and lm()
My commands are: nls(CV ~a*Est^b, data=limiares, start =list(a=100,b=0),
trace = TRUE) for nonlinear regression
The two methods are fitting different models. With lm(), the model is
y = a * x^b * error
or, equivalently,
ln(y) = ln(a) + b * ln(x) + ln(error)
With nls(), the model is
y = a * x^b + error
Thus you will get two different estimates.
Andy
From: Ana Quitério
Hi R users
I'm
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From: [EMAIL PROTECTED] [SMTP:[EMAIL PROTECTED] On Behalf Of Ana Quitério
Sent: Wednesday, January 25, 2006 3:33 PM
To: r-help@stat.math.ethz.ch
Subject: [R] Question about fitting power
From: Ana Quitério
Hi R users
I'm trying to fit a model y
