« Changelog History


PyMC v3.3 Release Notes

Release Date: 2018-01-09 // over 6 years ago

  • 🆕 New features

    • Improve NUTS initialization advi+adapt_diag_grad and add jitter+adapt_diag_grad (#2643)
    • ➕ Added MatrixNormal class for representing vectors of multivariate normal variables
    • Implemented HalfStudentT distribution
    • 🆕 New benchmark suite added (see http://pandas.pydata.org/speed/pymc/)
    • 👀 Generalized random seed types
    • ⚡️ Update loo, new improved algorithm (#2730)
    • 🆕 New CSG (Constant Stochastic Gradient) approximate posterior sampling algorithm (#2544)
    • 👀 Michael Osthege added support for population-samplers and implemented differential evolution metropolis (DEMetropolis). For models with correlated dimensions that can not use gradient-based samplers, the DEMetropolis sampler can give higher effective sampling rates. (also see PR#2735)
    • 👍 Forestplot supports multiple traces (#2736)
    • ➕ Add new plot, densityplot (#2741)
    • 🗄 DIC and BPIC calculations have been deprecated
    • 🔨 Refactor HMC and implemented new warning system (#2677, #2808)

    🛠 Fixes

    • 🛠 Fixed compareplot to use loo output.
    • 👌 Improved posteriorplot to scale fonts
    • sample_ppc_w now broadcasts
    • df_summary function renamed to summary
    • ➕ Add test for model.logp_array and model.bijection (#2724)
    • Fixed sample_ppc and sample_ppc_w to iterate all chains(#2633, #2748)
    • ➕ Add Bayesian R2 score (for GLMs) stats.r2_score (#2696) and test (#2729).
    • SMC works with transformed variables (#2755)
    • Speedup OPVI (#2759)
    • 🛠 Multiple minor fixes and improvements in the docs (#2775, #2786, #2787, #2789, #2790, #2794, #2799, #2809)

    🗄 Deprecations

    • 🚚 Old (minibatch-)advi is removed (#2781)