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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.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.