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mixtur: Modelling Continuous Report Visual Short-Term Memory Studies

A set of utility functions for analysing and modelling data from continuous report short-term memory experiments using either the 2-component mixture model of Zhang and Luck (2008) <doi:10.1038/nature06860> or the 3-component mixture model of Bays et al. (2009) <doi:10.1167/9.10.7>. Users are also able to simulate from these models.

Version: 1.2.1
Depends: R (≥ 4.0)
Imports: dplyr, ggplot2, rlang, tidyr
Suggests: knitr, rmarkdown
Published: 2023-04-06
DOI: 10.32614/CRAN.package.mixtur
Author: Jim Grange ORCID iD [aut, cre], Stuart B. Moore ORCID iD [aut], Ed D. J. Berry [ctb]
Maintainer: Jim Grange <grange.jim at gmail.com>
BugReports: https://github.com/JimGrange/mixtur/issues
License: GPL-3
Copyright: Some functions have been adapted from Matlab code written by Paul Bays (https://bayslab.com) published under GNU General Public License.
URL: https://github.com/JimGrange/mixtur
NeedsCompilation: no
Materials: README NEWS
CRAN checks: mixtur results

Documentation:

Reference manual: mixtur.pdf

Downloads:

Package source: mixtur_1.2.1.tar.gz
Windows binaries: r-devel: mixtur_1.2.1.zip, r-release: mixtur_1.2.1.zip, r-oldrel: mixtur_1.2.1.zip
macOS binaries: r-release (arm64): mixtur_1.2.1.tgz, r-oldrel (arm64): mixtur_1.2.1.tgz, r-release (x86_64): mixtur_1.2.1.tgz, r-oldrel (x86_64): mixtur_1.2.1.tgz
Old sources: mixtur archive

Reverse dependencies:

Reverse suggests: bmm

Linking:

Please use the canonical form https://CRAN.R-project.org/package=mixtur to link to this page.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.