[BUG] Development Factors #578
cynthiatchetagni
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Hi @cynthiatchetagni, welcome and thanks so much for the question! I looked at the sample data set that you posted, which is super helpful, it makes debugging so much easier. The Try this: cl.Development(average = "simple").fit(sinistreINC)Does this help? Do you get the numbers you expect now? |
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Hi Kenneth,
Thank you so much for your answer and thank you for this amazing package!
I am still exploring it and hope to be a crack on it
Best regards,
Cynthia
Le ven. 7 mars 2025 à 02:12, Kenneth S. Hsu ***@***.***> a
écrit :
… Hi @cynthiatchetagni <https://github.com/cynthiatchetagni>, welcome and
thanks so much for the question!
I looked at the sample data set that you posted, which is super helpful,
it makes debugging so much easier.
The cl.Development() estimator by default estimates LDFs/CDFs using
volume-weighted averages. If you want the estimate to reconcile to the
numbers you calculated in your excel workbook, you will need to pass in an
additional parameter. More details here
<https://chainladder-python.readthedocs.io/en/master/library/generated/chainladder.Development.html>
.
Try this:
cl.Development(average = "simple").fit(sinistreINC)
Does this help? Do you get the numbers you expect now?
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<#552 (comment)>
Hi @cynthiatchetagni <https://github.com/cynthiatchetagni>, welcome and
thanks so much for the question!
I looked at the sample data set that you posted, which is super helpful,
it makes debugging so much easier.
The cl.Development() estimator by default estimates LDFs/CDFs using
volume-weighted averages. If you want the estimate to reconcile to the
numbers you calculated in your excel workbook, you will need to pass in an
additional parameter. More details here
<https://chainladder-python.readthedocs.io/en/master/library/generated/chainladder.Development.html>
.
Try this:
cl.Development(average = "simple").fit(sinistreINC)
Does this help? Do you get the numbers you expect now?
—
Reply to this email directly, view it on GitHub
<#552 (comment)>,
or unsubscribe
<https://github.com/notifications/unsubscribe-auth/AOT3CQCNYYBBV25TP6WSJDD2TDW7BAVCNFSM6AAAAABX7TDOG2VHI2DSMVQWIX3LMV43OSLTON2WKQ3PNVWWK3TUHMZDOMBVGI4DSNRRGY>
.
You are receiving this because you were mentioned.Message ID:
***@***.***>
--
Cynthia Tchetagni
"Scan globally and reinvent locally" J.Stiglitz
"La pensée complexe est une pensée qui cherche à la fois à distinguer mais
sans disjoindre et à relier tout en distinguant" E.Morin
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Describe the bug
while calculating manually my chainladder development factors, I do not have the same results with the .ldf_
To Reproduce
import chainladder as cl
print("pandas: " + pd.version)
print("numpy: " + np.version)
print("chainladder: " + cl.version)
sinistreINC = cl.Triangle(sinistres,origin="origin",development="development",columns="values", cumulative=False)
sinistreINC = sinistreINC.grain("OYDY")
sinistreINC
sinistreINC.link_ratio
sinistreINC.age_to_age.heatmap()
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