Package: dyadicMarkov 0.1.3.9000

Mattia Böllenrücher

dyadicMarkov: Pattern Estimation and Identification for Dyadic Sequences Using Transition Matrices in R

Provides methods for analyzing categorical dyadic sequences using transition matrices within the Longitudinal Actor-Partner Interdependence Model and Markov-chain framework. The package supports empirical transition counts, maximum likelihood estimation of transition probabilities, and identification of univariate and bivariate patterns of interaction in dyadic sequences.

Authors:Mattia Böllenrücher [aut, cre, cph], Mégane Bollenrücher [aut], Jean-Philippe Antonietti [aut]

dyadicMarkov_0.1.3.9000.tar.gz
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manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
dyadicMarkov/json (API)

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

Reviews:rOpenSci Software Review #()

Bug tracker:https://github.com/boellenruecherm/dyadicmarkov-public/issues

Pkgdown/docs site:https://boellenruecherm.github.io

Datasets:

On CRAN:

Conda:

apimcategorical-datadyadic-datalongitudinal-datatransition-matrices

5.30 score 321 downloads 7 exports 0 dependencies

Last updated from:96bd1d421b (on ropensci-review-refinements). Checks:10 OK. Indexed: no.

TargetResultTimeFilesSyslog
linux-develOK162
pkgdown docsOK225
source / vignettesOK234
linux-releaseOK146
macos-releaseOK115
macos-oldrelOK97
windows-develOK89
windows-releaseOK76
windows-oldrelOK90
wasm-releaseOK115

Exports:bivariateCasecompletePatterncountEmpcountEmpBivariatemleEstimationpartialPatternunivariatePattern

Dependencies:

Bivariate dyadic workflow
Overview | Data | Empirical bivariate transition counts | Global bivariate case | Local pattern identification for a complete case | Repeating the analysis from each perspective | Reading the global and local steps together | References
Rendered frombivariate-workflow.Rmdusingknitr::rmarkdown

Last update: 2026-09-15
Started: 2026-06-20

Introduction to dyadicMarkov
Purpose of the package | Real-world use cases | Data structure | Estimation and identification | Exported functions | Assumptions and current scope | Relationship to the workflow vignettes | References
Rendered fromdyadicMarkov-introduction.Rmdusingknitr::rmarkdown

Last update: 2026-09-15
Started: 2026-06-20

Sensitivity analysis
Overview | Data | Univariate worked example | Bivariate worked example | Sequence-length sensitivity results | Interpretation | References
Rendered fromsensitivity-analysis.Rmdusingknitr::rmarkdown

Last update: 2026-09-15
Started: 2026-09-15

Univariate dyadic workflow
Overview | Data | Empirical transition counts | Maximum-likelihood transition probabilities | Univariate pattern identification | Interpretation | References
Rendered fromunivariate-workflow.Rmdusingknitr::rmarkdown

Last update: 2026-09-15
Started: 2026-06-20