-nl- offers a solution but it is NOT a good one. I have tested it with
data from the cited paper below and have been found lacking.
Here is one reason why we fit two-line models rather than a smooth curve:
In examining the relationship between two linear metabolic variables,
as a person exercise we can detect the time at which this person
changes form aerobic to anaerobic state (i.e. change in slope). That
point is what we refer to as the changepoint. Here interest lies in
estimating the changepoint.
The Statistician (2001). 50, Part 1, 51-61.
I am a bit disappointed though that Stata is still lagging behind.
Raphael
On Jan 31, 2008 3:27 PM, Nick Cox <[email protected]> wrote:
> I don't understand what distinction is being made here.
>
> My understanding is that nonlinear least squares is one flavour of
> numerical optimisation. Whether -nl- is an especially good way to
> proceed with the broken stick problem I cannot say, but on the face of
> it that is one clear solution.
>
> In any event Mata now includes much more on numerical optimisation than
> was available in 2005, so Raphael has several approaches to choose from
> in writing his program.
>
> I'll insert my own prejudice: it seems to me that if broken stick really
> is an appropriate model, rather than something smoother, then the
> breakpoint will be fairly obvious in any case, at least in terms of an
> initial value.
>
> Nick
> [email protected]
>
> Raphael Fraser
>
> I saw a thread with the above subject line concerning
> piecewise linear regression posted in 2005 on Statalist.
> I am facing the same problem now; that of estimating the unknown
> change point. Mention was made of using -nl- but it uses
> least squares method. The only way to solve this problem
> is numerical optimization. The problem can be solved
> quite easily in SAS using NLIN PROC.
> Is there a Stata solution?
>
>
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