masc 0.1.0

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.