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.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.Sigma_true argument generates stimuli with a
specified correlation structure (a matrix, or a single uniform
off-diagonal correlation).hotelgluth2024 dataset from the hotel-choice
experiment.