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: 1.2.0
Depends: R (≥ 4.0)
Imports: dplyr, ggplot2, rlang, tidyr, RColorBrewer
Suggests: knitr, rmarkdown
Published: 2021-08-03
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_1.2.0.tar.gz
Windows binaries: r-devel: mixtur_1.2.0.zip, r-release: mixtur_1.2.0.zip, r-oldrel: mixtur_1.2.0.zip
macOS binaries: r-release (arm64): mixtur_1.2.0.tgz, r-release (x86_64): mixtur_1.2.0.tgz, r-oldrel: mixtur_1.2.0.tgz

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