generalized-additive-models
Generalized Additive Models in Python. (by tommyod)
statsmodels
Statsmodels: statistical modeling and econometrics in Python (by statsmodels)
generalized-additive-models | statsmodels | |
---|---|---|
1 | 8 | |
13 | 9,591 | |
- | 1.4% | |
7.0 | 9.4 | |
3 months ago | 1 day ago | |
Python | Python | |
BSD 3-clause "New" or "Revised" License | 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.
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.
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
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[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
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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.
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How do you usually build your models?
Since you are using python, pandas, scikit-learn, scipy, and statsmodels are what you are looking for
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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?