Package: masc 0.1.0.9000

Kiante Fernandez

masc: Simulate the Multi-Attribute Search and Choice (MASC) Model

Simulates the Multi-Attribute Search and Choice (MASC) model of Gluth, Deakin and Rieskamp (2026) <doi:10.1037/rev0000614> for multi-attribute decision-making, including sequential information search, Bayesian belief updating, and choice. Beliefs may be treated as univariate (independent attributes), or multivariate over correlated attributes ('MASC-C'), in which observing one attribute updates beliefs about correlated attributes via a Kalman filter.

Authors:Kiante Fernandez [aut, cre, cph]

masc_0.1.0.9000.tar.gz
masc_0.1.0.9000.zip(r-4.7-x86_64)masc_0.1.0.9000.zip(r-4.7-arm64)masc_0.1.0.9000.zip(r-4.6-x86_64)masc_0.1.0.9000.zip(r-4.6-arm64)masc_0.1.0.9000.zip(r-4.5-x86_64)
masc_0.1.0.9000.tgz(r-4.6-x86_64)masc_0.1.0.9000.tgz(r-4.6-arm64)masc_0.1.0.9000.tgz(r-4.5-x86_64)masc_0.1.0.9000.tgz(r-4.5-arm64)
masc_0.1.0.9000.tar.gz(r-4.7-arm64)masc_0.1.0.9000.tar.gz(r-4.7-x86_64)masc_0.1.0.9000.tar.gz(r-4.6-arm64)masc_0.1.0.9000.tar.gz(r-4.6-x86_64)
masc_0.1.0.9000.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
masc/json (API)

# Install 'masc' in R:
install.packages('masc', repos = c('https://kiante-fernandez.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/kiante-fernandez/masc/issues

Uses libs:
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3
Datasets:

On CRAN:

Conda:

openblascpp

5.38 score 2 stars 24 scripts 303 downloads 1 exports 2 dependencies

Last updated from:b469361288. Checks:15 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-arm64OK131
linux-devel-x86_64OK154
source / vignettesOK301
linux-release-arm64OK134
linux-release-x86_64OK153
macos-release-arm64OK111
macos-release-x86_64OK345
macos-oldrel-arm64OK88
macos-oldrel-x86_64OK334
windows-devel-arm64OK348
windows-devel-x86_64OK157
windows-release-arm64OK352
windows-release-x86_64OK123
windows-oldrel-x86_64OK116
wasm-releaseOK113

Exports:rMASC

Dependencies:RcppRcppArmadillo

Attribute Weights and Attention with Varying Sampling Noise

Last update: 2026-05-20
Started: 2025-04-23

MASC Parameters and Reward Rate

Last update: 2026-05-20
Started: 2025-04-23

Overall Value and Predicted Number of Fixations

Last update: 2026-05-20
Started: 2025-04-23

Response Time and The Number of Options

Last update: 2026-05-20
Started: 2025-04-23

Simulating Time Pressure with Varying Levels of Search Sensitivity

Last update: 2026-05-20
Started: 2025-04-23