f the produces one error: singular gradient matrix at early parameter estimates.

You are watching: Singular gradient matrix at initial parameter estimates

The result is roughly a = 1.1466, b = 0.6415, so there shouldn"t be a difficulty with intial parameter estimates as i have characterized them as a=1, b=0.5.

I have actually read in other topics that it is convenient to modify the curve. Ns was thinking about something prefer log y=log a *(b^x), however I don"t know just how to deal with role specification. Any type of idea?

r curve-fitting nls
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edited Feb 17 "14 in ~ 0:44
inquiry Feb 16 "14 at 18:44

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I will increase my comment into an answer.

If I usage the following:

y or

(m i obtain:

As for automatically generating starting values, i am not acquainted with a procedure to execute that. One technique I have read around is to simulate curves and use beginning values that generate a curve that shows up to approximate your data.

Here is the plot produced using the above parameter estimates using the following code. I recognize that possibly the lower right section of the line might fit a little better:

setwd("c:/users/mmiller21/simple R programs/")jpeg(filename = "nlr.plot.jpeg")plot(x,y) curve(1.0934^(0.7242^x), from=0, to=11, add=TRUE)dev.off()


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edited Feb 17 "14 in ~ 1:29
reply Feb 17 "14 at 0:59

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