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One option is the nls function as @SvenHohenstein suggested. Another option is to convert your nonlinear regression into a linear regression. In the case of this equation just take the log of both sides of the equation and do a little algebra and you will have a linear equation. You can run the regression using something like: fit <- lm( log(y) ~ log(x1) + log(x2), data=mydata) The intercept ...
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