Cameron Davidson-Pilon

Wow that's awesome. Sure I'll write something up for you

The `potential` function is an implicit part of the model (in fact, all `potential` functions are implicit parts of the model: the can define relationships between the random variables). So...

Allen Downy, of Think Bayes, used this example in his book, of which you can read online [here](http://www.greenteapress.com/thinkbayes/html/thinkbayes007.html) That may help

Looking at how pandas uses bottleneck, it's not a strict dependency, but highly recommended: https://pandas.pydata.org/pandas-docs/stable/install.html#recommended-dependencies So I'm a bit torn. I think I will require it. Going back to our...

👋 @TristanBoudreault okie! But clearly this behaviour is poorly documented, so I'm going to reopen this issue with a docs tag.

Hi @Foreist, can you provide more details about what you mean by "consider censorship and survival the same"?

Hi @aflatouniana, I was able to replicate the results locally: ### Python: ```python ll = LogLogisticAFTFitter() ll.fit(df, "spell", "event", formula="logwage + ui + age") ll.print_summary(decimals=4, columns=["coef", "exp(coef)"]) """ duration col...

Hi @arturomoncadatorres, looks very interesting. I'll give it a look later this week!

Hi @sokol11, hm, not at the moment. The hazard is not directly estimated, so you would need to take the diff of the cumulative hazard and apply a smoothing function...

Hi @daniyalshahzad, I assuming you're getting an inf with `predict_median` (judging by the SO question you posted). This is unexpected, as we internally compute the median [explicitly](https://github.com/CamDavidsonPilon/lifelines/blob/master/lifelines/fitters/log_normal_aft_fitter.py#L156). Does your code...