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piecewise linear regression

David Winsemius 
It actually looked reasonably economical but the output certainly is  
ugly. I see a variety of approaches in the r-help archives. This  
thread discusses two other approaches, degree-one splines from Berry  
and hard coded-coefficients from Lumley:

http://finzi.psych.upenn.edu/R/Rhelp08/archive/118046.html

The Lumley solution has the advantage which he articulates that the  
slopes are more directly interpretabel and in this case you can see  
that yourversion's year slope agrees with Lumley's suggested  
parametrization:

 > m=lm(percent~ year + pmax(year,1996) + pmin(year, 1996), weights=1/ 
se,
+ subset=year>=1988, da=d);
 > m

Call:
lm(formula = percent ~ year + pmax(year, 1996) + pmin(year, 1996),      
data = d, subset = year >= 1988, weights = 1/se)

Coefficients:
      (Intercept)              year  pmax(year, 1996)  pmin(year, 1996)
        1161.3126           -0.2177           -0.3494                NA

More compact output to boot.

Thread (4 messages)

David Freedman piecewise linear regression Mar 7 David Winsemius piecewise linear regression Mar 7 Rolf Turner piecewise linear regression Mar 8 vito muggeo piecewise linear regression Mar 9