On Thu, 18 Apr 2019 10:36:10 +0000
akshay kulkarni <akshay...@hotmail.com> wrote:
> fx <- (x1 <= -2)*(x1^2) + (x1 > -2 && x1 < 2)*(x1^3) + (x1 > =
> 2)*(x1^4)
>
> Can I include fx in an nls call to create something like this:
>
> NLS1 <- nls(y ~ a*(sin(x2) + fx), start = list(a = 2)) ?
For now, you can, since fx does not depend on any of the parameters you
optimize in the nls() call. (Actually, the model as presented should be
solveable by lm(y ~ I(sin(x2) + fx) + 0), since it is linear in its
only parameter.)
If you make fx a function and use ifelse() to provide different
outcomes depending on a condition in a vectorized fashion, you would
make it easier to add new parameters later, should the need arise:
fx <- function(x1, x2)
ifelse(x1 <= -2, EXPR_IF_TRUE..., EXPR_IF_FALSE...)
NLS1 <- nls(y ~ a*(sin(x2) + fx(x1, x2)), ...)
--
Best regards,
Ivan
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