Changes in version 2.1.0                        

  - The four kernel functions are consolidated into one: RBFKernel() now
    takes derivative orders d_i and d_j (0 = function value, 1 = first
    derivative; default 0) and covers the value-value, value-derivative,
    derivative-value, and derivative-derivative cases itself.
    RBFKernel_01(), RBFKernel_11(), and RBFKernel_All() are removed.
    Results are unchanged: the new function performs the identical
    arithmetic, verified bit-for-bit against 2.0.0 at the kernel,
    posterior, and full seed-matched experiment level.
  - DESCRIPTION reference formatted per CRAN guidance (year added,
    quotes removed from acronyms).

                 Changes in version 2.0.0 (2026-09-09)                  

First public release of the streamlined package, extracted from the
replication code for Weaver, Kumar, and Jain, "Nonparametric Pricing
Bandits Leveraging Informational Externalities to Learn the Demand
Curve" (Marketing Science).

  - PricingBandit(): single entry point running one pricing experiment
    with any of six policies ("UCB", "TS", "GP-UCB", "GP-TS",
    "GP-UCB-M", "GP-TS-M"), a user-supplied willingness-to-pay vector,
    and an arbitrary price grid.
  - Heterogeneous-noise extension (hetero = TRUE) available for all
    Gaussian process variants, and periodic history resets (reset) for
    time-varying demand.
  - Lightweight run diagnostics (GetDiagnostics()) counting how often
    numerical fallback paths fired; the counters draw no random numbers,
    so results are unaffected.
  - num_knots defaults to 11 for the monotonic variants regardless of
    the number of arms (larger values can destabilize the truncated
    sampler).
  - The truncated-sampling timeout (default 5 seconds per attempt) is a
    user-settable argument of PricingBandit().
  - Results validated seed-for-seed bit-identical against the paper's
    replication code for all policies.