Replies: 3 comments 10 replies
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Hi @son1403, Can you post the data set here please? Or as an alternative, would you be able to replicate the error using one of the sample datatset included in the package? |
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Hey I am also haveing similar challenges: I did check valuations, and looks ok,although I have future valuations as well. dont know if that is the problem |
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@Obalus2022 , this looks odd, but I cannot reproduce. Using the data visible in your screenshot, I get ldfs consistent with the link ratio triangle: On the valuation vector, it does include dates for the unfilled lower half of your triangle, so the future dates you are seeing is normal. reprex code: import chainladder as cl
import pandas as pd
from io import StringIO
print('chainladder version: ', cl.__version__)
data = """
Idx,Acc,Dev,PDLALAE
PMP,2017,2017,449684
PMP,2018,2018,764067
PMP,2019,2019,428453
PMP,2020,2020,1334759
PMP,2021,2021,1316392
PMP,2017,2018,1485157
PMP,2018,2019,1918224
PMP,2019,2020,2357146
PMP,2020,2021,5503980
PMP,2017,2019,2086793
PMP,2018,2020,2042970
PMP,2019,2021,2871223
PMP,2017,2020,2267049
PMP,2018,2021,2081615
PMP,2017,2021,2444177
"""
Triangles = cl.Triangle(
pd.read_csv(StringIO(data)),
origin='Acc', development='Dev',
index='Idx', columns='PDLALAE',
cumulative=True)
dev = cl.Development(average='volume').fit(
Triangles.loc['PMP', 'PDLALAE', :, :]
)
dev.ldf_ |
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I am trying to calculate ldf & cdf to my development. My triangle show as below:
dev = cl.Development(average = "simple").fit(los_2021)
is okay but when i rundev.ldf_
, i get the errorValueError: Shape of passed values is (1, 45), indices imply (1, 16)
Could anyone help me with this? Thank you
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