Is it possible to specify that one parameter must be larger than another parameter in an nls call in my R script?
Here's my nls call:
fit <- nls(y ~ ifelse(g, m1 * (x - x0) + y0, m2 * (x - x0) + y0), start = c(m1 = -1, m2 = 1, y0 = 0, x0 = split), algorithm = "port", lower = c(m1 = -Inf, m2 = -Inf, y0 = -Inf, x0 = split), upper = c(m1 = Inf, m2 = Inf, y0 = Inf, x0 = (split+1)), data=data.frame(x,y)) It is finding values for the parameters m1, m2, x0, and y0. But I want to require that m2 must be LARGER than m1. How can I do this?
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Best Answer
No.
However it seems you are using nls in a wrong way — it will never work with non-differentiable functions. Can't you just fit two linear models to both parts of the data (i.e. data.frame(x,y)[g,] and data.frame(x,y)[!g,])?
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