Package: DstarM 0.5.0

Don van den Bergh

DstarM: Analyze Two Choice Reaction Time Data with the D*M Method

A collection of functions to estimate parameters of a diffusion model via a D*M analysis. Build in models are: the Ratcliff diffusion model, the RWiener diffusion model, and Linear Ballistic Accumulator models. Custom models functions can be specified as long as they have a density function.

Authors:Don van den Bergh [aut, cre], Stijn Verdonck [aut], Francis Tuerlinckx [aut]

DstarM_0.5.0.tar.gz
DstarM_0.5.0.tar.gz(r-4.7-arm64)DstarM_0.5.0.tar.gz(r-4.7-x86_64)DstarM_0.5.0.tar.gz(r-4.6-arm64)DstarM_0.5.0.tar.gz(r-4.6-x86_64)
DstarM_0.5.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
DstarM/json (API)
NEWS

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

Bug tracker:https://github.com/vandenman/dstarm/issues

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

On CRAN:

Conda:

openblascpp

1.93 score 17 scripts 610 downloads 1 mentions 24 exports 36 dependencies

Last updated from:134139e242. Checks:6 OK. Indexed: no.

TargetResultTimeFilesSyslog
linux-devel-arm64OK144
linux-devel-x86_64OK158
source / vignettesOK212
linux-release-arm64OK156
linux-release-x86_64OK153
wasm-releaseOK127

Exports:battacharyyachisqchisqFitDensityestCdfestDstarMestNDestObservedestQdfgetPdfsgetStergetTerhellingerLBA.densitynormalizeobsQuantilesplotObservedrtDescriptivesrtHistsimDatatestFunupgradeDstarMVoss.densityWiener.density

Dependencies:clicpp11DEoptimevdexpmfarvergenericsggplot2gluegslgtableisobandlabelinglatticelifecyclemagrittrMatrixmsmmvtnormpillarpkgconfigR6RColorBrewerRcppRcppArmadillorlangrtdistsRWienerS7scalessurvivaltibbleutf8vctrsviridisLitewithr