Changelog

ReliaLearnR 0.5

CRAN release: 2026-05-27

New rbd() tutorial covering Reliability Block Diagrams and system reliability, including series, parallel, mixed, and k-out-of-n configurations, system MTTF calculation, and an introduction to Fault Tree Analysis — with 4 code exercises and 12 quiz questions.
New rs() tutorial covering Repairable Systems Analysis, including Non-Homogeneous Poisson Process (NHPP) modeling, Mean Cumulative Function (MCF) estimation, and failure prediction.
Added a companion book to supplement the interactive tutorials.

All tutorials deepened with more exercises and quiz questions:
- RAM: Added an interactive failure rate (λ) slider, a Weibull bridge section, and 3 new exercises on series/parallel system reliability.
- LDA: Added an Anderson-Darling goodness-of-fit section with 2 quiz questions and a model comparison exercise; 2 additional code exercises.
- RS: Added 3 code exercises covering NHPP fitting, MCF plotting, and failure prediction.
- RT: Added 3 code exercises covering Duane plotting, RGA, and the Arrhenius acceleration factor.
NHPP tutorial updated to a MCF-first workflow for a more intuitive learning progression.
Added DiagrammeR-based visual diagrams to the RBD tutorial.

CRAN release: 2026-01-06

The package has been renamed from WeibullR.learnr to ReliaLearnR to better reflect its broader focus on reliability engineering topics beyond just Weibull analysis.
All functions and tutorials have been updated to use the new package name ReliaLearnR.
The WeibullR.learnr() function has been renamed to lda() to simplify its usage.
The TestR.learnr() function has been renamed to rt() to simplify its usage.
The RAMR.learnr() function has been renamed to ram() to simplify its usage.
All references to WeibullR.learnr in documentation and vignettes have been updated to ReliaLearnR.