distfit
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erdogant
distfit is a python library for probability density fitting.
Good day! Guys, I have found your package really cool) Thanks a lot) I have a question: Our incoming data can be with anomalies, noise. So, quality of our results...
What a really awesome repository ! By the way, K distribution is widely used in the filed of Radar and sonar. It is necessary to estimate the parameters of the...
Hello everyone, I noticed in the code `erdogant/distfit/distfit.py` that whenever you use the KS statistical test (`stats=ks`), you call the `scipy.stats.ks_2samp` to test your data against the distribution you estimated...
This is great work. What about 2D distribution fitting ? Like 2D bi-variate gaussian ?
Despite of well structure inside the only one .py file, it is actually not a good practice. I faced an issue on my own and made a comparison of my...
There may be some potentially significant speed improvements by running code that is compiled. At first glance, it seems that there doesn't exist a fit method in [numba-stats](https://pypi.org/project/numba-stats/) so that...
In insurance or other scenarios, we need to fit with zero truncated and zero modified theoretical distributions.
Use distfit to find the best theoretical distribution for the claim cost data dfit = distfit(todf=True) result = dfit.fit_transform(cost) dfit.plot(chart='pdf')
Hello, Maybe it can be helpful for you, the new version of fast Bootstrap implemented by the Spotify team. It can be beneficial to avoid computationally expensive bootstraps in distfit...
i really like this package, thanks for the implementation and support @erdogant Is there any plans to support Gaussian Mixture distributions as well? I think it would be really helpful...
