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A home for new additions to PyMC, which may include unusual probability distribitions, advanced model fitting algorithms, or any code that may be inappropriate to include in the pymc repository, but may want to be made available to users.

Uploaded Mon Mar 31 01:12:30 2025
md5 checksum 3ae67e07aa613ccc6d25e407e5e8d031
arch x86_64
build py39h06a4308_0
depends pymc >=5.6.0, python >=3.9,<3.10.0a0, scikit-learn
license Apache-2.0
license_family APACHE
md5 3ae67e07aa613ccc6d25e407e5e8d031
name pymc-experimental
platform linux
sha1 93c6d44e55581608c35a89d8512d1c72b2f59556
sha256 11acc6f6047972591d61a585cb0b7c83ec2bd093a6b7f91a1f139747cfab6d52
size 139702
subdir linux-64
timestamp 1690984897082
version 0.0.9