GLM.jl VS generalized-additive-models

Compare GLM.jl vs generalized-additive-models and see what are their differences.

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GLM.jl generalized-additive-models
2 1
574 13
1.2% -
5.0 7.0
26 days ago 3 months ago
Julia 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.

GLM.jl

Posts with mentions or reviews of GLM.jl. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2022-12-30.

generalized-additive-models

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

What are some alternatives?

When comparing GLM.jl and generalized-additive-models you can also consider the following projects:

MLJ.jl - A Julia machine learning framework

pgmpy - Python Library for learning (Structure and Parameter), inference (Probabilistic and Causal), and simulations in Bayesian Networks.

DSGE.jl - Solve and estimate Dynamic Stochastic General Equilibrium models (including the New York Fed DSGE)

pyhf - pure-Python HistFactory implementation with tensors and autodiff

RegressionTables.jl - Journal-style regression tables

pandas-profiling - Create HTML profiling reports from pandas DataFrame objects [Moved to: https://github.com/ydataai/pandas-profiling]

ARCHModels.jl - A Julia package for estimating ARMA-GARCH models.

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

ScikitLearn.jl - Julia implementation of the scikit-learn API https://cstjean.github.io/ScikitLearn.jl/dev/

statsmodels - Statsmodels: statistical modeling and econometrics in Python

MixedModels.jl - A Julia package for fitting (statistical) mixed-effects models

ydata-profiling - 1 Line of code data quality profiling & exploratory data analysis for Pandas and Spark DataFrames.