Add icdf for LogitNormal

[jnetzel1]

What is this PR about?
Adds ICDF functions to Logit Normal Distribution

Issue #6612

References:
Logit Normal:
https://en.wikipedia.org/wiki/Logit-normal_distribution

SciPy Implementations:
https://docs.scipy.org/doc/scipy/reference/generated/scipy.special.expit.html
https://github.com/scipy/scipy/blob/d604a5462dadf799f8af2c177179a01875b40796/scipy/stats/_continuous_distns.py#L380

Checklist

• Checked that the pre-commit linting/style checks pass
• Included tests that prove the fix is effective or that the new feature works
• Added necessary documentation (docstrings and/or example notebooks)
• If you are a pro: each commit corresponds to a [relevant logical change]

Type of change

• New feature / enhancement
• Bug fix
• Documentation
• Maintenance
• Other (please specify):

---

📚 Documentation preview 📚: https://pymc--7916.org.readthedocs.build/en/7916/

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[ricardoV94]

@jnetzel1 I pushed some changes to automatically derive icdf (and logp/logcdf) for this simple distribution. There's no longer a native LogitNormal but a CustomDist

[ricardoV94]

Small note: It isn't really undefined, just doesn't have a closed form solution

[codecov]

Codecov Report

❌ Patch coverage is 75.00000% with 4 lines in your changes missing coverage. Please review.
✅ Project coverage is 86.85%. Comparing base (3a0186e) to head (68d255e).
⚠️ Report is 9 commits behind head on main.

Files with missing lines	Patch %	Lines
pymc/distributions/continuous.py	66.66%	4 Missing ⚠️

Additional details and impacted files

@@            Coverage Diff             @@
##             main    #7916      +/-   ##
==========================================
- Coverage   91.47%   86.85%   -4.63%     
==========================================
  Files         116      116              
  Lines       18947    18929      -18     
==========================================
- Hits        17332    16441     -891     
- Misses       1615     2488     +873     

Files with missing lines	Coverage Δ
pymc/distributions/moments/means.py	0.00% <ø> (-100.00%)	⬇️
pymc/logprob/transforms.py	95.43% <100.00%> (+0.02%)	⬆️
pymc/distributions/continuous.py	67.69% <66.66%> (-30.56%)	⬇️

... and 10 files with indirect coverage changes

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[ricardoV94]

I moved this approach to #7956