OneShotEM
Efficient eM-Algorithm for One-Shot Device Data Analysis
Implements the simple and efficient Expectation-Maximization (eM) algorithm proposed by Zhu, Li, Li, and Balakrishnan (2026) <doi:10.1080/03610918.2025.2515193> for parameter estimation in one-shot device accelerated life testing (ALT) data. Unlike traditional EM algorithms that impute exact failure times, this method treats failure counts between inspection intervals as missing data, resulting in faster convergence and enhanced numerical stability. Supports Exponential, Weibull, Lognormal, Gamma, and custom user-defined lifetime distributions under log-linear stress models. Standard errors, confidence intervals, model selection statistics (AIC, BIC, AICc, HQIC), residual diagnostics, and visualization tools are provided. References: Balakrishnan and Ling (2012) <doi:10.1016/j.csda.2011.09.010>, Fan, Balakrishnan, and Chang (2009) <doi:10.1080/00949650802142592>.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
0.1.0 |
rolling linux/jammy R-4.5 | OneShotEM_0.1.0.tar.gz |
113.2 KiB |
0.1.0 |
rolling linux/noble R-4.5 | OneShotEM_0.1.0.tar.gz |
113.0 KiB |
0.1.0 |
rolling source/ R- | OneShotEM_0.1.0.tar.gz |
39.4 KiB |
0.1.0 |
latest linux/jammy R-4.5 | OneShotEM_0.1.0.tar.gz |
113.2 KiB |
0.1.0 |
latest linux/noble R-4.5 | OneShotEM_0.1.0.tar.gz |
113.0 KiB |
0.1.0 |
latest source/ R- | OneShotEM_0.1.0.tar.gz |
39.4 KiB |
0.1.0 |
2026-04-23 source/ R- | OneShotEM_0.1.0.tar.gz |
0 B |