covid19model VS pgmpy

Compare covid19model vs pgmpy and see what are their differences.

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covid19model pgmpy
2 2
943 2,599
-0.4% 1.8%
0.0 8.1
almost 3 years ago 7 days ago
Stan Python
MIT License MIT 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.

covid19model

Posts with mentions or reviews of covid19model. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2022-01-17.

pgmpy

Posts with mentions or reviews of pgmpy. We have used some of these posts to build our list of alternatives and similar projects.

We haven't tracked posts mentioning pgmpy yet.
Tracking mentions began in Dec 2020.

What are some alternatives?

When comparing covid19model and pgmpy you can also consider the following projects:

causalnex - A Python library that helps data scientists to infer causation rather than observing correlation.

statsmodels - Statsmodels: statistical modeling and econometrics in Python

scikit-learn - scikit-learn: machine learning in Python

rustworkx - A high performance Python graph library implemented in Rust.

CausalPy - A Python package for causal inference in quasi-experimental settings

pyhf - pure-Python HistFactory implementation with tensors and autodiff

Lottery-Simulation - This program can simulate a number of drawings in the Lottery (6 out of 49). The guesses and the draws are chosen randomly and the user can choose how many right guesses there should be (0-6). Then the program will run through the simulation as many times as it takes to get the exact number of correct guesses the user chose. The user can also choose how many times this should be repeated (the higher the number, the more accurate the result will be). Then the program will automatically calculate the average number of tries it took to get the chosen number of correct guesses and tell the user the chance of getting this certain number of correct guesses.

dodiscover - [Experimental] Global causal discovery algorithms

generalized-additive-models - Generalized Additive Models in Python.

auton-survival - Auton Survival - an open source package for Regression, Counterfactual Estimation, Evaluation and Phenotyping with Censored Time-to-Events

HumesGuillotine - Hume's Guillotine: Beheading the social pseudo-sciences with the Algorithmic Information Criterion for CAUSAL model selection.

machinelearnjs - Machine Learning library for the web and Node.