chainladder-python
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casact
Actuarial reserving in Python
I noticed a minor issue when reserving using the Cape Cod. When incurred or paid loss is $0 for an accident period, the Cape Cod method will predict $0 of...
Hello, I received the following traceback when trying to run the .valuation_correlation method: ``` Traceback (most recent call last): File "/usr/lib/python3.10/code.py", line 90, in runcode exec(code, self.locals) File "", line...
Grain is throwing the exception for OY and DY for the below input. **triangle.grain(OYDY)** 2019-12-15 2019-12-31 2300000.0000 2019-12-21 2019-12-31 5000000.0000 2018-12-29 2018-12-31 3542379.0000 2018-12-28 2018-12-31 10400000.0000 2018-12-30 2018-12-31 1000000.0000 2019-12-27...
Hello, I have some origin and development data that are in a semester format (example : 2021-S1). I converted the data by changing YYYY-S1 to YYYY-01-01 and YYYY-S2 to YYYY-07-01....
error at the bottom of the page `plt.plot( (model_cl.ultimate_["Paid"]).to_frame().index.astype("string"), (model_cl.ultimate_["Paid"] / model_cl.ultimate_["reportedCount"]).to_frame(), )` `plt.xticks(np.arange(0, 10 * 12, 12), np.arange(2008, 2018, 1))`
I get a different answer depending on whether I fit just the work comp LOB vs all LOBs and then slice work comp. These approaches should yield the same answer,...
If the a `DevelopmentConstant()` takes in ldfs, and the triangle applied is smaller (or shorter in length) than the constant, the rest of the constant is discarded. Sample code: ```python...
offending code: ```python import chainladder as cl import pandas as pd data = [['2010-01-01', '2011-06-30', 'premium', 100.0], ['2010-01-01', '2011-12-31', 'incurred', 100.0], ['2010-01-01', '2012-06-30', 'premium', 200.0], ['2010-01-01', '2012-12-31', 'incurred', 100.0], ['2010-01-01',...
The second issue in #159, the `CaseOutstanding()` method can only hand "Approach 1", as demonstrated by [Friedland](https://www.casact.org/sites/default/files/database/studynotes_friedland_estimating.pdf), page 265 (or 271 by count). We are missing Approach 2, as discussed...
abc = cl.load_sample('abc') len(abc.origin) len(abc.development) len(abc.valuation) model = cl.BarnettZehnwirth(formula='C(origin)+C(development)+C(valuation)').fit(abc)
