PyMC
Bayesian Modeling and Probabilistic Programming in Python (by pymc-devs)
statsmodels
Statsmodels: statistical modeling and econometrics in Python (by statsmodels)
Our great sponsors
| PyMC | statsmodels | |
|---|---|---|
| 3 | 8 | |
| 8,142 | 9,513 | |
| 1.2% | 1.9% | |
| 9.4 | 9.4 | |
| 1 day ago | 7 days ago | |
| Python | Python | |
| GNU General Public License v3.0 or later | BSD 3-clause "New" or "Revised" License |
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
PyMC
Posts with mentions or reviews of PyMC.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2021-09-06.
- PYMC Release: v5.0.0
-
An Astronomer's Introduction to NumPyro
I believe the pymc versions were resolved into developing version 4 of pymc. Development at https://github.com/pymc-devs/pymc
It still depends on theano now evolved and renamed
-
What is Probabilistic Programming?
This tutorial explains what is probabilistic programming & provides a review of 5 frameworks (PPLs) using an example taken from Chapter 4 of Statistical Rethinking by Dr. Richard McElreath. Frameworks (PPLs) reviewed are - Stan (https://mc-stan.org/) PyMC3 (https://docs.pymc.io/) Tensorflow Probability (https://www.tensorflow.org/probability) Pyro/NumPyro (https://pyro.ai/) Turing.jl (https://turing.ml/stable/) I also provide the basic review of a great library called arviz (https://arviz-devs.github.io/arviz/), which can be used for all the above-mentioned PPLs to do Exploratory Data Analysis of Bayesian Models. Here is the link to the notebook in which I have implemented the example model using the above Frameworks/PPLs https://colab.research.google.com/drive/1zgR2b0j2waGi1ppnIe1rw7emkbBXtMqF?usp=sharing
statsmodels
Posts with mentions or reviews of statsmodels.
We have used some of these posts to build our list of alternatives
and similar projects.
- statsmodels Release Candidate 0.14.0rc0 tagged
- How to generate Errors using Scipy Minimize with Powell Method
-
[P] statsmodels.tsa.holtwinters.ExponentialSmoothing results in NaN forecasts and parameters when fitting on entire dataset using known parameters from training model.
I reckon you're more likely to get a good response on their Github page than here. Unless a dev happens to see this post.
- Statsmodels 0.13.3 released with Python 3.11 support
-
First Year UG here, can someone offer any coding advice?
The method they use for computing the parameter covariance (in the code here, around line 330) involves some linear algebra, as they use the Moore-Penrose pseudo-inverse of the outputs.
-
How do you usually build your models?
Since you are using python, pandas, scikit-learn, scipy, and statsmodels are what you are looking for
-
Advice required to choose appropriate software for an assignment
Can't you get a student discount for Stata? R would definitely be able to handle everything. For Python, have a look through the statsmodel package https://github.com/statsmodels/statsmodels
- [C] I have an MS in Statistics - how can I get better at coding?
What are some alternatives?
When comparing PyMC and statsmodels you can also consider the following projects:
Dask - Parallel computing with task scheduling
SciPy - SciPy library main repository
stan - Stan development repository. The master branch contains the current release. The develop branch contains the latest stable development. See the Developer Process Wiki for details.
Numba - NumPy aware dynamic Python compiler using LLVM
SymPy - A computer algebra system written in pure Python
Pandas - Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more
pyro - Deep universal probabilistic programming with Python and PyTorch
orange - 🍊 :bar_chart: :bulb: Orange: Interactive data analysis