Hi:

Perhaps something like

f1(x, y) * I(z > 0) + f2(x, y) * I(z <= 0)      ??

HTH,
Dennis

On Fri, Mar 11, 2011 at 3:10 AM, Otto Kässi <otto.kassi@gmail.com> wrote:

> Dear r-helpers,
>
> This might be an elementary question, but I have a hard time getting
> my head around it, so all help is much appreciated.
>
> I am working on a nonlinear regression model of the form
>
> if z > 0
> y = f1(x,y),
> else
> y = f2(x,t) .
>
> In other words, the functional form of f(.) changes according to some
> criteria z. Natural approach would be to fit two models, i.e.
> model1 <- nlm(y ~ ..., data=data[data$z > 0,]),
> model2 <- nlm(y ~ ..., data=data[data$z <= 0,]).
> But this is unfeasible since both models contain the same variable x
> and I would like to estimate the coefficient on x using both subsets
> of the data.
>
> My first shot would be to do something like this:
> formula <- ifelse(z > 0, "y ~ f(x,y).", "y ~ f(x,t)")
> nlm(formula, data=data)
>
> .. but preliminary testing indicates that this might not work. The
> coefficient on t does not get estimated.
>
> Thanks in advance for all helpful suggestions!
>
> With kind regards,
> Otto
>
> ----
> Otto Kassi
> University of Helsinki
> Dept. of Economics
>
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