NEWS
hdMTD 0.1.4 (2025-12-18)
Fixes and improvements
- Simplified the S3 class hierarchy: fitted objects of class
MTDest now inherit from MTD.
- Removed redundant class checks from S3 methods, relying on method dispatch.
- Eliminated duplicated S3 methods (
coef.MTDest, probs.MTDest), which now work via inheritance.
- Streamlined plotting code: overlapping plot types in
plot.MTDest are delegated to plot.MTD using NextMethod().
- Simplified
summary() methods by printing directly from the summary output, removing auxiliary summary-print classes.
- Reorganized internal helper functions (e.g., moved
PI() and sx() from utils.R to dedicated files).
- Improved and consolidated user-facing documentation, explicitly listing available S3 methods and accessors in the constructors’ help pages.
hdMTD 0.1.3 (2025-11-01)
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 (2025-09-28)
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 (2025-08-27)
- Relicensed the package from MIT to GPL-3.
- Removed an unintended
README.md file from the package source.