posteriordb 1.1.0

This release expands PosteriorDB with broader PyMC support, additional reference posterior draws, new summary statistics, and several model/specification fixes.

Highlights

• Added 73 PyMC model implementations under posterior_database/models/pymc.
• Added the new posterior/model variant M0_data-M0_model_discrete.
• Added 11 new reference posterior draw objects, increasing the total from 46 to 57.
• Added corresponding mean_value and mean_squared_value summary statistics.
• Updated model metadata with PyMC implementation information and version metadata.
• Updated citation metadata to the AISTATS 2025 PosteriorDB paper.
• Added Croissant metadata and updated licensing information.

Fixes and Improvements

• Fixed the Covid posterior specification.
• Fixed a gradient issue in dogs_hierarchical.
• Aligned priors or standard deviations in selected diamonds, earnings, kidiq, and mesquite models.
• Fixed Stan argument types in IRT models.
• Improved PyMC model idiomaticity and import structure.

Validation

Before release, we checked that:

• check_pdb(pdbl, run_stan_code_checks = FALSE) passes.
• All 120 Stan model files parse successfully with rstan::stanc().

What's Changed

• Fixing GLMM_Poisson model prior by @JTorgander in #276
• fixing typos by @JTorgander in #275
• Update citation in README by @avehtari in #280
• converting string to float by @JTorgander in #283
• updating caching version by @JTorgander in #282
• updating caching version by @JTorgander in #281
• Prerelease V1.0 by @MansMeg in #288
• Update development by @MansMeg in #296
• Fix argument type in 2pl_latent_reg_irt by @avehtari in #295
• Adding reference draws for "rate" and "dogs" models by @JTorgander in #291
• Adding ref draws round 2 by @JTorgander in #302
• Revert "Adding ref draws round 2" by @JTorgander in #304
• Adding ref draws round 2b by @JTorgander in #305
• Adding ref draws - round 3 by @JTorgander in #306
• Add the arma11 model by @Ch0ronomato in #270
• Implement Binomial GLM model in PyMC by @ricardoV94 in #265
• Implement Poisson GLM model in PyMC by @PellelNitram in #267
• FIXES model info typo by @JTorgander in #314
• Implement earnings-height model in pymc by @jessegrabowski in #269
• Eight schools noncentered model in PyMC by @fonnesbeck in #264
• PyMC implementation of M0 model by @fonnesbeck in #266
• Fix spec of covid posterior by @dannys4 in #324
• Add 68 idiomatic PyMC model implementations by @twiecki in #319

New Contributors

• @Ch0ronomato made their first contribution in #270
• @ricardoV94 made their first contribution in #265
• @PellelNitram made their first contribution in #267
• @jessegrabowski made their first contribution in #269
• @fonnesbeck made their first contribution in #264
• @dannys4 made their first contribution in #324
• @twiecki made their first contribution in #319

Full Changelog: 1.0.0...1.1.0