HDNRA 2.1.0

New features

Added WZ2026.GLHTBF.2cNRT(), an F-type normal-reference test for heteroscedastic high-dimensional general linear hypothesis testing (GLHT) problems.
WZ2026.GLHTBF.2cNRT() supports the grouped-data GLHTBF interface WZ2026.GLHTBF.2cNRT(Y, G, n, p), where Y is a list of groupwise data matrices, G is the raw full-row-rank contrast matrix, n is the vector of group sample sizes, and p is the common data dimension.
The new GLHTBF F-type routine implements a trace-studentized quadratic contrast statistic with Welch–Satterthwaite two-cumulant F-type normal-reference calibration.
The returned NRtest object reports the test statistic, p-value, fitted numerator and denominator degrees of freedom, and the corresponding approximation method.
The new GLHTBF F-type routine can be used for both omnibus one-way MANOVA-type hypotheses and targeted rank-one contrast hypotheses through the same grouped-data interface.
Added CCXH2024.GLHTBF.2cNRT() for the rank-one scale-invariant GLHTBF normal-reference procedure of Cao et al. (2024).
Added LHNB2025.GLHTBF.NABT() for the rank-one random-integration GLHTBF normal-approximation procedure of Li et al. (2025).

Updated the GLHTBF documentation to clarify that the software argument G is the raw contrast matrix supplied by the user; the normalized contrast matrix and the induced contrast operator are constructed internally.
Added examples showing how to call WZ2026.GLHTBF.2cNRT() for omnibus and rank-one GLHTBF analyses using grouped data.
Updated the method inventory so that the newly added GLHTBF routines are listed under the correct problem class and calibration family.
Updated references to the proposed statistic TNEW so that its callable routine is consistently recorded as WZ2026.GLHTBF.2cNRT().
Expanded package references and documentation entries for the newly added GLHTBF procedures.

Standardized input validation for the new GLHTBF routines, including checks on the groupwise data list Y, contrast matrix G, sample-size vector n, and common dimension p.
Improved consistency of returned approximation fields across GLHTBF normal-reference routines.
Kept the new F-type implementation inversion-free and compatible with HDLSS settings where the sample covariance matrices may be singular.
Updated exported functions, manual pages, examples, and package metadata for the new GLHTBF additions.
Improved consistency between the package description, method inventory, documentation, and simulation workflow.

Fixed minor documentation inconsistencies in GLHTBF examples and method descriptions.
Fixed possible mismatches between newly exported GLHTBF function names, examples, and test scripts.
Corrected minor typographical and formatting issues in package documentation.

Renamed the function BS1996.TS.NART to BS1996.TS.NABT for consistency.
Fixed several typos in the documentation and function names.
Corrected several typographical errors in the documentation and function names to improve clarity and usability.
Replaced deprecated save-always with actions/cache@v3 in GitHub Actions workflow.
Enhanced GitHub Actions performance by implementing caching for R package dependencies, leading to faster build times and improved CI efficiency.

The function name has been changed. The title, example, output format of the function have been changed, and some typos have also been corrected.
Added a helper function to ‘HDNRA.cpp’ file in order to improve computation speed; updated the code of all functions to facilitate faster computation.
Added an ‘NRtest.object’ to output an S3 class ‘NRtest’ for our package, and also constructed a corresponding print function to output the appropriate format.
Added a ‘zzz.R’ file to manage package startup messages and initialization.