I have data of the price of a product before a newer version came out and after a newer version came out. I'd like to model the slope of the product pre the new product, and post the new product.
Looking at the data, it is obvious when this point is and the negative slope over time for the product increases in magnitude.
Linear models did not make much sense, since intercepts are different and not realistic?
Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) 668.12155 2.25824 295.86 <2e-16 *** pre -0.23071 0.01968 -11.72 <2e-16 ***
POST (after day 150):
Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) 821.00351 10.96838 74.85 <2e-16 *** post -1.13929 0.04899 -23.25 <2e-16 ***
Any advice on how to deal with this problem would be helpful.