Hello, R users,
I applied segmented regression method contributed by Muggeo and got
different slope estimates depending on the initial break points. The results
are listed below and I'd like to know what is a reasonable approach handling
this kinds of problem. I think applying various initial break points is
certainly not a efficient approach. Is there any other methods to deal with
segmented regression? From a graph, v shapes are more clear at 1.2 and 1.5
break points than 1.5 and 1.7. Appreciate your help.

Result1: 
Initial break points are 1.2 and 1.5. The estimated break points and slopes:

 Estimated Break-Point(s):
                 Est.      St.Err
Mean.Vel 1.285     0.05258
               1.652    0.01247  
              
               Est.          St.Err.             t value        CI(95%).l
CI(95%).u
slope1   0.4248705     0.3027957   1.403159    -0.1685982        1.018339
slope2   2.3281445     0.3079903   7.559149     1.7244946        2.931794
slope3   9.5425516     0.7554035   12.632390     8.0619879       11.023115 
Adjusted R-squared: 0.9924.

Result2:
Initial break points are 1.5 and 1.7. The estimated break points and slopes:

Estimated Break-Point(s):
                Est.       St.Err
Mean.Vel 1.412      0.02195
               1.699      0.01001
           
               Est.          St.Err.        t value            CI(95%).l
CI(95%).u
slope1  0.7300483   0.1381587    5.284129       0.4592623      1.000834
slope2  3.4479466   0.2442530    14.116289     2.9692194       3.926674
slope3 12.5000000   1.7783840     7.028853     9.0144314      15.985569

Adjusted R-squared: 0.995. 




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