Changes in version 0.1.0.9000                      

                 Changes in version 0.1.0 (2026-05-27)                  

First public release.

  - rMASC() simulates the Multi-Attribute Search and Choice (MASC) model
    of Gluth, Deakin and Rieskamp (2026) — sequential information
    search, Bayesian belief updating, and choice.
  - New Sigma_belief argument enables the multivariate MASC-C belief
    update: when the assumed correlation structure is non-diagonal,
    observing one attribute updates beliefs about correlated attributes
    via a Kalman filter ("belief spread"). With a diagonal or NULL
    Sigma_belief the model reduces exactly to the original univariate
    MASC update.
  - New Sigma_true argument generates stimuli with a specified
    correlation structure (a matrix, or a single uniform off-diagonal
    correlation).
  - Bundled hotelgluth2024 dataset from the hotel-choice experiment.