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dyadicMarkov 0.1.3

• Added a sensitivity-analysis vignette reproducing the published sequence-length analysis for 1,000 simulated dyads at five sequence lengths, with shorter worked examples for 30- and 90-point sequences.
• Added the fixed simulation datasets used in the sensitivity analysis and documented their structure, binary state space, historical labels, and separate simulation at each sequence length.
• Clarified the terminology used in the sensitivity analysis and noted the small numerical differences from the published sensitivity and specificity results.
• Documented how exact AIC ties are handled in partial and complete bivariate pattern selection.
• Improved validation of the digits argument used by print, summary, and LaTeX methods.
• Added a check for state-space sizes that are too large to construct the required transition-count matrices safely.
• Updated the statistical-software-review annotations to reflect the legacy implementation parity tests.
• Added and updated tests for the changes above.
• Added base-R state-strip plot() methods for univariate pattern results and binary bivariate case and pattern results, with accessible defaults and retained sequence metadata.
• Added inferential summary tables and LaTeX representations for empirical-count and MLE matrices.

dyadicMarkov 0.1.2

• Clarified that the univariate pattern-identification procedure is an LRT procedure evaluated using Pearson Chi-squared, while the global bivariate nested-model/LRT framework implements two chi-squared tests for A1 and B1, also evaluated using Pearson Chi-squared.
• Clarified that local bivariate pattern selection computes the G-squared deviance before applying AIC = G^2 + 2k.
• Corrected the univariate pattern-identification and global bivariate case boundaries so that p-values equal to alpha are treated as rejection (p <= alpha).
• Documented that the univariate workflow supports multiple categorical states, while the bivariate workflow is defined for two dichotomous variables.
• Added focused tests that distinguish Pearson’s chi-squared statistic from G-squared and verify both partial and complete bivariate AIC paths.
• Updated the maintainer email address and package version for this release.
• Made the manual simulated-parity script stop when a comparison fails.
• Declared srr as a development/documentation dependency.

dyadicMarkov 0.1.1

• Updated package wording and metadata for the CRAN submission.
• Added S3 classes and print/summary support for pattern and case identification results.
• Added S3 classes for empirical count matrices and MLE transition probability matrices while preserving ordinary matrix behavior.
• Added two synthetic 90-point example datasets for package workflow examples.
• Rewrote the workflow vignette around the built-in univariate and bivariate example datasets.
• Improved internal input validation for count, estimation, and pattern-identification functions.
• Updated tests and documentation for the new S3 return objects.
• Improved validation for extreme state-space inputs, non-finite chain values, and malformed empirical matrices.
• Refactored selected internal validation and AIC helper code to reduce function complexity while preserving exported behavior.
• Improved bivariate count validation coverage for unsupported and malformed inputs.

dyadicMarkov 0.1.0

• Initial CRAN submission.

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