Package: MLCM 0.4.3

Guillermo Aguilar

MLCM: Maximum Likelihood Conjoint Measurement

Conjoint measurement is a psychophysical procedure in which stimulus pairs are presented that vary along 2 or more dimensions and the observer is required to compare the stimuli along one of them. This package contains functions to estimate the contribution of the n scales to the judgment by a maximum likelihood method under several hypotheses of how the perceptual dimensions interact. Reference: Knoblauch & Maloney (2012) "Modeling Psychophysical Data in R". <doi:10.1007/978-1-4614-4475-6>.

Authors:Ken Knoblauch [aut], Laurence T. Maloney [aut], Guillermo Aguilar [aut, cre]

MLCM_0.4.3.tar.gz
MLCM_0.4.3.tar.gz(r-4.5-noble)MLCM_0.4.3.tar.gz(r-4.4-noble)
MLCM_0.4.3.tgz(r-4.4-emscripten)MLCM_0.4.3.tgz(r-4.3-emscripten)
MLCM.pdf |MLCM.html
MLCM/json (API)
NEWS

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

Peer review:

Datasets:
  • BumpyGlossy - Conjoint Measurement Data for Bumpiness and Glossiness
  • GlossyBumpy - Conjoint Measurement Data for Bumpiness and Glossiness
  • Texture - Three-way Conjoint Measurement Data for Texture Regularity.

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

1.70 score 1 stars 1 scripts 343 downloads 1 mentions 8 exports 0 dependencies

Last updated 3 years agofrom:0d68015cca. Checks:OK: 1 NOTE: 1. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 01 2024
R-4.5-linuxNOTENov 01 2024

Exports:as.mlcm.dfbinom.diagnosticsboot.mlcmmake.widemake.wide.fullmlcmmlcm.defaultmlcm.formula

Dependencies: