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### Description
Multivariate adaptive regression splines
### Purpose
Output similar to ordinary regression for high dimensional data. The method allows testing of non-linear associations alon…
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### Is there an existing issue for this?
- [X] I have searched the existing issues
### Problem description
[Checks](https://forum.freecad.org/viewtopic.php?t=5236):
1) Latest development ver…
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[NLInteraction--pub](https://projecteuclid.org/journals/annals-of-applied-statistics/volume-14/issue-1/Estimating-the-health-effects-of-environmental-mixtures-using-Bayesian-semiparametric/10.1214/19-…
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I am using `pygam.gam( )` that is fitting all the features with splines (without my imposing any specific `term` to any feature), so is it fair to say that GAM is equivalent to multivariate adaptive r…
ghost updated
4 years ago
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Right now the code is using thin plate splines with 'k' specified. The approach is described well here: https://stats.stackexchange.com/questions/486109/gams-specifying-knots-positions-for-thin-plate-…
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You cover LOESS, polynomials and breakpoint modelling nonlinear patterns, but oddly do not cover splines (breakpoint modelling is a subset of regression splines limited to linear, slope = 0 models) in…
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(another random thought, a quick google search shows that there is some information, but I haven't read anything.)
In the illustrative quantile regression example, I used heteroscedasticity to get …
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aside: pygam has penalized Expectile regression according to the examples/documentation
Currently RLM and QuantileRegression only use a IRLS algorithm
For RLM we can add gradient fit with scipy …
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Hi,
Is it possible to include the function that conducts spline regression in the Riemann manifold? I read a paper "Smoothing splines on Riemannian manifolds, with applications to 3D shape space" pub…
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Optimize wiggliness through lambda so that the residuals of the alternative model equal zero.
This would eliminate the instances where RSS of the null model < RSS alt model. (?)