formula formatting/grammar for regression
This is just (or should be) just a simple example of what I would like to extend to further regression - which is why I was looking for a resource on the grammar. If I try: lm(ypts ~ exp(xpts)), I only get an intercept and one coefficient. And for the coefficient, I am not sure where that should go? (ie is that A or r in the formula y=A*exp(r*x) ) Also, when I tried to use nls, I get an error: nls(ypts ~ exp(xpts)) Error in getInitial.default(func, data, mCall = as.list(match.call(func, : no 'getInitial' method found for "function" objects If someone could please point out what I am doing wrong, or point me to a good resource on this, I would greatly appreciate it. Thanks!
Dieter Menne wrote:
Brigid Mooney <bkmooney <at> gmail.com> writes:
I am doing some basic regression analysis, and am getting a bit confused on how to enter non-polynomial formulas to be used.
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But am confused on what the formula should be for trying to find a fit to y = A*exp(r*x).
If this example is just a placeholder for "more complex than poly", you should check function nls which works for non-linear functions. However, if you really want to solve this problem only, doing a log on you data and fitting a log of the above function with lm() is the easiest way out. Results can be a bit different from the nonlinear case depending on noise, because in one case weight are log-weighted, in the other linearly. Dieter
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