https://ian-weaver.r-universe.devRecent package updates in ian-weaverR-universehttps://github.com/ian-weaver.pnghttps://ian-weaver.r-universe.devThu, 10 Sep 2026 11:07:43 GMTweaver.n.ian@gmail.com (Ian N. Weaver)Implements multi-armed bandit approaches for pricing experiments with an unknown demand curve, as developed in Weaver, Kumar, and Jain (2025) "Nonparametric Pricing Bandits Leveraging Informational Externalities to Learn the Demand Curve" <doi:10.1287/mksc.2022.0247>. Includes Upper Confidence Bound (UCB) and Thompson Sampling (TS) baselines, Gaussian process variants (GP-UCB, GP-TS), monotonic Gaussian process variants that constrain demand to be weakly decreasing in price, and heterogeneous-noise extensions. The willingness-to-pay distribution is fully user-specified via a vector of consumer valuations, so any demand environment can be simulated or replayed.https://github.com/r-universe/ian-weaver/actions/runs/38148850827Thu, 10 Sep 2026 11:07:43 GMTPricingBandits2.1.0successhttps://ian-weaver.r-universe.devhttps://github.com/ian-weaver/pricingbanditspricingbandits-intro.Rmdpricingbandits-intro.htmlGetting Started with PricingBandits2026-08-27 08:03:092026-09-10 10:15:33