hdMTD 0.1.3

Fixes

• Modified the tie-breaking rule in the FS (Forward Selection) procedure to ensure deterministic behavior.
• Updated MTD-methods, MTDest-methods and MTD-accessors documentation to remove redundant links in the help system and streamline method listings.
• Sample size is now a required argument in perfectSample().
• Improved the error message in logLik.MTD() when a sample is not provided.

New Features

• Added a plot.MTD() method for visualizing MTD models, including bar plots of lag contributions and mixture weights, as well as directed weighted graphs (via igraph) representing each lag-specific transition matrix.
• Added a plot.MTDest() method for fitted MTDest objects, which mirrors plot.MTD() but also includes EM iteration diagnostics (log-likelihood variation per update) when available.

hdMTD 0.1.2

New

• Accessor functions for “MTD”: pj(), p0(), lambdas(), lags(), Lambda(), states(), and transitP(). See ?MTD-accessors.
• Accessor functions for “MTDest”: pj(), p0(), lambdas(), lags(), S() and states(). See ?MTD-accessors.
• Accessor functions for “hdMTD”: S() and lags(). See ?MTD-accessors.
• Methods for “MTD” and “MTDest” objects: added print(), summary(), coef(), logLik() and probs(). For compact inspection of lag sets, state space, mixture weights and more. See ?MTD-methods and ?MTDest-methods.
• Methods for “hdMTD” objects: added print() and summary() for compact inspection of lag selection results. See ?hdMTD-methods.
• Coercion: new as.MTD() to rebuild an “MTD” object from an “MTDest” fit.

Changes

• probs() is now a S3 generic with methods for “MTD” and “MTDest”. Returns one-step-ahead predictive probabilities either for specific contexts (context=) or from sample rows (newdata=). If neither is supplied, it returns the full global transition matrix (transitP(object) for MTD; transitP(as.MTD(object)) for MTDest).
• Renamed the sample-based estimator probs(X, S, ...) to empirical_probs(X, S, ...) to avoid ambiguity: empirical_probs() estimates transition probabilities from data, while probs() returns predictive probabilities from model/fit objects.

Fixes

• Replaced any(is.na(X)) with anyNA(X) in checkSample() for efficiency and clarity.

Package cleanup

• Removed unused datasets (raindata, sleepscoring, testChains).
• Updated examples to use simulated data (via perfectSample()) instead of the removed testChains dataset.
• Internal helpers marked @keywords internal so they no longer appear in help(package="hdMTD").

hdMTD 0.1.1

• Relicensed the package from MIT to GPL-3.
• Removed an unintended README.md file from the package source.