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Can anyone give me a good explanation for what the parameter “algorithm” does in the nls function in R?
Also, how does the formula work? I know it uses a tilda, but I can’t really find a down-to-earth explanation of it.
Also, how important are the start values? Do I need to try multiple start values, or can I still have a guarantee that nls will find the correct parameters regardless of the start values I use?
In brief:
nls()is going to vary parameters to try to minimize the square error between your model and your data. There’s several good methods it can try to find the minimum. Reading the details about “method” in?optimwill provide some good info and references.In general, for nonlinear models, your results can be sensitive to initial guess. You should try several different guesses to make sure that the outputs are close. If your results are very sensitive to your guess, you can try re-parameterizing, using a different algorithm, or rethinking your model.
As for the formula, I’d echo the previous answer. Work through the examples in the bottom of
?nlsand then try to ask a more specific question.