Master's Project: Reliability Estimation in Series Systems
My master's project on maximum likelihood estimation for series systems with right-censored and masked failure data.
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My master's project on maximum likelihood estimation for series systems with right-censored and masked failure data.
Algebra over Probability Distributions
Algebraic Maximum Likelihood Estimators
Compositional Maximum Likelihood Estimation
Likelihood-Based Statistical Inference in the Fisherian Tradition
A retrospective on three years of building R packages and writing papers for masked series system reliability, and what comes next.
Observation functors in maskedcauses: composable functions that separate the data-generating process from the observation mechanism, enabling mixed-censoring simulation and verified Monte Carlo studies.
The maskedcauses R package for MLE in series systems with masked component failures, built on composable likelihood contributions and validated through simulation.
Extending masked failure data analysis when the standard C1-C2-C3 masking conditions are violated.
Closed-form MLEs and Fisher information for exponential series systems with masked failure data. No numerical optimization required.
Maximum likelihood estimation of component reliability from masked failure data in series systems, with BCa bootstrap confidence intervals validated through extensive simulation studies.
A generic R framework for composable likelihood models. Likelihoods are first-class objects that compose through independent contributions.
An R package that treats MLEs as algebraic objects. They carry Fisher information, compose through independent likelihoods, and propagate uncertainty correctly.