Tag archive
Statistics is full of formulas for confidence intervals, one per situation, each with assumptions you might be breaking. The bootstrap throws them all out and uses one idea instead, resample your data and watch. Here it is in a few lines of R.
k-means is the go-to clustering algorithm, two simple steps repeated until things settle. But the same data can give different clusters depending on where you start, and it will happily find groups that are not there. Here it is in R, honest about both.
The maskedcauses R package for MLE in series systems with masked component failures, built on composable likelihood contributions and validated through simulation.
My graduate coursework from SIUe's math program is up: time series, regression, computational stats, multivariate analysis, and statistical methods.
An R package that gives hypothesis tests a consistent interface. Every test returns the same structure. You can write generic code that works across all of them.
A generic R framework for composable likelihood models. Likelihoods are first-class objects that compose through independent contributions.
An R package that treats probability distributions as algebraic objects. They compose through standard operations. The algebra preserves distributional structure.
An R package for specifying hazard functions directly instead of picking from a catalog of named distributions. You write the hazard. It handles the rest.
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.
A retrospective on three years of building R packages and writing papers for masked series system reliability, and what comes next.
Extending masked failure data analysis when the standard C1-C2-C3 masking conditions are violated.