Most of the data sets I'm dealing with exhibit a time trend.
We would like to get rid of the time trend.
The plot shows in some cases a monotonic increase of the dependent variable
with time. This is the easiest case.
In some other cases the plot shows a time trend where the dependent variable
changes slope 4-5 times along the observations measurement period.

I've attempted a segmented regression and estimated the break-point
empirically. This is a tedious error-prone process.
I just found out that R includes a package, called "segmented",  which can
estimate the break-point discriminating between two regression models.
I have browsed through the on-line documentation. It is stated multiple
break-points are supported by "segmented".
However I cannot understand if a break-point per independent variable
(regressor) is handled when there are many independent variables in the
model, or if "segmented" can handle many breakpoints for the same
independent variable (time in my case) ... ?

I would greatly appreciate some explanations and suggestions on the use of
"segmented".

Thank you very much in advance.

Regards,

-- 
Maura E.M

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