Kenneth S. Hsu
Kenneth S. Hsu
Ahh, similar solution to what I came up with. ```python raa = cl.load_sample("raa") cl.Development().fit_transform(raa[raa.valuation.year >= raa.valuation_date.year-3]).link_ratio.heatmap() ``` I think I am getting better at this. Only problem is now we...
Yes, even better!
Yes, unless you think it's useful to add an argument to only heatmap the last n diagonals? It's a bit better as we can see the older diagonals that are...
That's actually a great idea. I like that. With this we should be able to see if the remaining LDFs have any patterns.
Is there a way to get the values out of `cl.DevelopmentConstant()`? ```python patterns = {12: 2, 24: 1.25, 36: 1.1, 48: 1.08, 60: 1.05, 72: 1.02} triangle_custompattern = cl.DevelopmentConstant( patterns=patterns,...
I actually think `.patterns` works, thanks!
The more I think about this, the more I feel like I shouldn't be using `.patterns`. Instead, `cl.DevelopmentConstant()` should have a `.ldf_` and `.cdf_` attributes that take consideration of `.patterns`...
In fact, from the [docstrings](https://chainladder-python.readthedocs.io/en/latest/modules/generated/chainladder.DevelopmentConstant.html), I think the intention was that we wanted `.ldf_` and `.cdf_`?
So does that mean that the docstring for `cl.DevelopmentConstant()` is not correct? There should be no attributes for `.ldf_` and `cdf_` since "parameters accessible pre-fit are hyperparameters and should not...
The more I work on this, the more I feel like this method should be coded as a pattern instead of an IBNR model. Let me try to summarize the...