Optimization of two linear models with constraint
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I have a dataset which is a 'v-shaped' pattern of dots: y_observed and want to adjust two linear regressions with a turning point TP so that a cost function minimices the errors for the to models, y_calc1=m1*x(1:TP)+b1, y_calc2=m2*x(TP:end)+b2 AND y_calc1(TP)=y_calc2(TP).
Can somebody help me with this? its a simple 'fmincon' problem
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Matt J
2012-10-6
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This should be applicable.
What you describe is a first order spline with a single free knot.
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2012-10-6
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