Adding one more method:
glm(y~ x1 + x2 + x3 - 1, family = gaussian(link = "inverse"), data = mydata)
will fit the exact model (including the desired error structure).
The default GLM starting values usually work OK, but it is true that
inverse-links can sometimes be more finicky than more typical links.
On 2023-08-19 6:48 p.m., John Fox wrote:
Dear John, John, and Paul,
In this case, one can start values by just fitting
> lm(1/y ~ x1 + x2 + x3 - 1, data=mydata)
Call:
lm(formula = 1/y ~ x1 + x2 + x3 - 1, data = mydata)
Coefficients:
x1 x2 x3
0.00629 0.00868 0.00803
Of course, the errors enter this model differently, so this isn't the
same as the nonlinear model, but the regression coefficients are very
close to the estimates for the nonlinear model.
Best,
John
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