Describe the issue linked to the documentation

Follows from #17387

Suggest a potential alternative/fix

Stop referencing preprocessing functions e.g. :

maxabs_scale
minmax_scale
normalize
quantile_transform
robust_scale
scale
power_transform

in the UG, and only add them e.g. in the "See Also" sections, or even just in the API ref.

In particular right now the first entr

Collection of follow-ups to #5827. These can/should be broken out into individual PRs. Many are relatively straightforward and would make a good first PR.

General

• Documentation (none was added in original PR).
• Release notes.
• Example notebook.
• Double-check how sm.tsa.arima.ARIMA works with fix_params (it should fail except when the fit method is statespace

Describe the issue linked to the documentation

Here is the link to the documentation file of Tomek Link
https://github.com/scikit-learn-contrib/imbalanced-learn/blob/6b3c5aed61f2e5dc0e8af87d97ea92b95dcafdd0/doc/under_sampling.rst

You write "In some other words, a Tomek’s link exist if the two samples are the nearest neighbors of each other. In the figure below, a Tomek’s link is illustra

See:
gonum/gonum#845 (comment)

In X-ray crystallography, the most important prior distributions include two special cases of the generalized gamma distribtion. I am very keen to try this parameterization of the variational distritribution in my research project. How hard would it be for the TFP devs to implement this distr

1. "Conclusion" section of "Getting started with Tablesaw" page contains broken link to "Java Docs".
   https://jtablesaw.github.io/tablesaw/gettingstarted#conclusion
2. "Exploring tables" section of "Getting started with Tablesaw" page contains broken link to "plotting".
   https://jtablesaw.github.io/tablesaw/gettingstarted.html#exploring-tables

I found several useful applications of pseudo-random number sampling in the past. In particular:

• Inverse transform sampling
• Gibbs sampling

(This issue serves a reminder to add the respective methods. Pull requests always welcome.)