Comments (6)
Hello!
The first graphs are just the functions 1-exp(-a*x) where a is the best saturation parameter.
The second row is c^x where c is the best carryover value, and the x are the integers from 0to 5.
Hope that helps!
Best
Robert
from mamimo.
Hi again!
thank you for your reply :)
I had asked for the plot code because I can not get them to appear exactly the same because in the saturation I get the price for the Radio is 7700 and yet in the graph appears values of 15000. I don't know if at the end you are adding the amount of each x weeks or if it is an aggregate sum of each week.
In the carryover graphs I don't know how you get this %. Do you do the percentage every 5 lags? or how?
Thank you for your kindness :)
Best
Rai
from mamimo.
Hi!
Well, you can decide the price range however you want. I chose 0 to 15000, but you can also make this range larger or smaller. I'm really just plotting 1-exp(-a*x) there, nothing more, nothing less. If a=0.0001, just plot 1-np.exp(-0.0001*x)
from x=0 to 15000, for example.
In the carryover, just do 0.5**np.arange(5)
and plot this as a bar chart if you wanna plot the carryover for 5 days, with a strength of 0.5. Then just format the y-Axis to percentages, and you are done.
Best
Robert
from mamimo.
Hi!
I think I understood perfectly the carriover graph :)
To finish, I understand that in the graphs of Baaners and Radio only appear 100% because the length in the optimization of hyperparameters is 0 no? understanding that only the advertising has only effect the first week
(0.5**np.arange(5))* np.array([1, 0, 0, 0, 0]))
in the case length = 0
(0.5**np.arange(5))* np.array([1, 1, 1, 0, 0]))
in the case length = 2
thank you very much :)
from mamimo.
On day 0, 100% of the spending effect is still in place. On day 1, only 100%*50%=50%. At day 2 only 100%*50%*50%=25%, etc. That's all that graphic says.
from mamimo.
Thank for you help! :)
from mamimo.
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