Package: dyadicMarkov 0.1.1
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:
dyadicMarkov_0.1.1.tar.gz
dyadicMarkov_0.1.1.zip(r-4.7)dyadicMarkov_0.1.1.zip(r-4.6)dyadicMarkov_0.1.1.zip(r-4.5)
dyadicMarkov_0.1.1.tgz(r-4.6-any)dyadicMarkov_0.1.1.tgz(r-4.5-any)
dyadicMarkov_0.1.1.tar.gz(r-4.7-any)dyadicMarkov_0.1.1.tar.gz(r-4.6-any)
dyadicMarkov_0.1.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
dyadicMarkov/json (API)
NEWS
| # Install 'dyadicMarkov' in R: |
| install.packages('dyadicMarkov', repos = c('https://boellenruecherm.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/boellenruecherm/dyadicmarkov-public/issues
Pkgdown/docs site:https://boellenruecherm.github.io
- dyadic_bivariate_example - Synthetic bivariate dyadic sequence example
- dyadic_univariate_example - Synthetic univariate dyadic sequence example
apimcategorical-datadyadic-datalongitudinal-datatransition-matrices
Last updated from:44caa2861b. Checks:9 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-x86_64 | OK | 124 | ||
| source / vignettes | OK | 147 | ||
| linux-release-x86_64 | OK | 123 | ||
| macos-release-arm64 | OK | 80 | ||
| macos-oldrel-arm64 | OK | 74 | ||
| windows-devel | OK | 73 | ||
| windows-release | OK | 72 | ||
| windows-oldrel | OK | 68 | ||
| wasm-release | OK | 92 |
Exports:bivariateCasecompletePatterncountEmpcountEmpBivariatemleEstimationpartialPatternunivariatePattern
Dependencies:
Bivariate dyadic workflow
Rendered frombivariate-workflow.Rmdusingknitr::rmarkdownon Jun 21 2026.Last update: 2026-06-21
Started: 2026-06-20
Introduction to dyadicMarkov
Rendered fromdyadicMarkov-introduction.Rmdusingknitr::rmarkdownon Jun 21 2026.Last update: 2026-06-21
Started: 2026-06-20
Univariate dyadic workflow
Rendered fromunivariate-workflow.Rmdusingknitr::rmarkdownon Jun 21 2026.Last update: 2026-06-21
Started: 2026-06-20
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Bivariate case identification for dyadic Markov chains | bivariateCase |
| Complete bivariate pattern identification by AIC | completePattern |
| Empirical transition counts for univariate dyadic sequences | countEmp |
| Empirical transition counts for bivariate dyadic sequences | countEmpBivariate |
| Synthetic bivariate dyadic sequence example | dyadic_bivariate_example |
| Synthetic univariate dyadic sequence example | dyadic_univariate_example |
| Maximum likelihood estimation of transition probabilities | mleEstimation |
| Partial bivariate pattern identification by AIC | partialPattern |
| Univariate pattern identification for dyadic Markov chains | univariatePattern |
