[R] R nls results different from those of Excel ??

[Jeff Newmiller]

Excel definitely does not use nonlinear least squares fitting for power curve fitting. It uses linear LS fitting of the logs of x and y. There should be no surprise in the OP's observation.
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Sent from my phone. Please excuse my brevity.

Greg Snow <538280 at gmail.com> wrote:

>Have you plotted the data and the lines to see how they compare?  (see
>fortune(193)).
>
>Is there error around the line in the data?  The nls function is known
>to
>not work well when there is no error around the line.   Also check and
>make
>sure that the 2 methods are fitting the same model.
>
>You might consider taking the log of both sides of the function to turn
>it
>into a linear function and using lm to fit the logs.
>
>
>On Mon, Feb 18, 2013 at 9:49 PM, David Gwenzi <dgwenzi at gmail.com>
>wrote:
>
>> Hi all
>>
>> I have a set of data whose scatter plot shows a very nice power
>> relationship. My problem is when I fit a Power Trend Line in an Excel
>> spreadsheet, I get the model y= 44.23x^2.06 with an R square value of
>0.72.
>> Now, if I input the same data into R and use
>> model< -nls(y~ a*x^b , trace=TRUE, data= my_data, start = c(a=40,
>b=2)) I
>> get a solution with a = 246.29 and b = 1.51. I have tried several
>starting
>> values and this what I always get. I was expecting to get a value of
>a
>> close to 44 and that of b close to 2. Why are these values of a and b
>> so different from those Excel gave me. Also the R square value for
>the nls
>> model is as low as 0.41. What have I done wrong here? Please help.
>Thanks
>> in advance
>>
>> David
>>
>>         [[alternative HTML version deleted]]
>>
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