python-mle
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ibab
A Python package for performing Maximum Likelihood Estimates
I ran the example from [README.md](https://github.com/ibab/python-mle/blob/master/README.md) and it does not work because the implementation of the implicit import is wrong. Currently, the problem with the implicit import of mle is...
Is there a type 2 maximum likelihood estimate？
When installing via pip, the sub-modules (distributions, ...) are not installed. Some googling tells me that this might be because the sub-packages are not listed in the `setup.py`: http://stackoverflow.com/questions/15368054/import-error-on-installed-package-using-setup-py https://docs.python.org/2/distutils/examples.html#pure-python-distribution-by-package
Googling i.e. "python maximum likelihood" often brings up this repository, altough [tensorprob](https://github.com/tensorprob/tensorprob) seems to be the successor of this project. This could be clearly marked in the README.
## Constraints These are nothing special i suppose, we just need an operator to join likelihoods with different data sizes. I think the logical approach for the end user for...
When only a certain range of the data is used for the fit, or when a range has been cut out, the PDFs need to be adjusted accordingly by removing...
- [ ] Polynomial - [ ] Chebyshev Polynomials - [ ] Exponential - [ ] Mix extended #7 - [ ] Crystal Ball - [ ] Novosibirsk - [...
We should be able to easily sample data from the model.
Currently we're using [OptimizeResult](http://docs.scipy.org/doc/scipy/reference/generated/scipy.optimize.OptimizeResult.html#scipy.optimize.OptimizeResult) from scipy when returning results. The idea is to have an object that basically behaves like a dictionary, but also pretty-prints the results and various useful...