Package: MLCM 0.4.4
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:
MLCM_0.4.4.tar.gz
MLCM_0.4.4.tar.gz(r-4.7-any)MLCM_0.4.4.tar.gz(r-4.6-any)
MLCM_0.4.4.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
MLCM/json (API)
| # Install 'MLCM' in R: |
| install.packages('MLCM', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
- 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.
Last updated from:56dfe90e8e. Checks:4 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-x86_64 | OK | 102 | ||
| source / vignettes | OK | 178 | ||
| linux-release-x86_64 | OK | 98 | ||
| wasm-release | OK | 100 |
Exports:as.mlcm.dfbinom.diagnosticsboot.mlcmmake.widemake.wide.fullmlcmmlcm.defaultmlcm.formula
Dependencies:
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Maximum Likelihood Conjoint Measurement | MLCM-package MLCM |
| Analysis of Deviance for Maximum Likelihood Conjoint Measurement Model Fits | anova.mlcm |
| Coerce data frame to mlcm.df | as.mlcm.df |
| Diagnostics for Binary GLM | binom.diagnostics plot.mlcm.diag |
| Resampling of an Estimated Conjoint Measurement Scale | boot.mlcm |
| Conjoint Measurement Data for Bumpiness and Glossiness | BumpyGlossy GlossyBumpy |
| Fitted Responses for a Conjoint Measurement Scale | fitted.mlcm |
| Extract Log-Likelihood from mlcm Object | logLik.mlcm |
| Create data frame for Fitting Conjoint Measurment Models by glm | make.wide make.wide.full |
| Fit Conjoint Measurement Models by Maximum Likelihood | mlcm mlcm.default mlcm.formula print.mlcm |
| Plot an mlcm Object | lines.mlcm plot.mlcm points.mlcm |
| Create Conjoint Proportion Plot from mlcm.df Object | plot.mlcm.df |
| Predict Method for MLCM Objects | predict.mlcm |
| Summary Method for mlcm objects | print.summary.mlcm summary.mlcm |
| Three-way Conjoint Measurement Data for Texture Regularity. | Texture |