Reliability

symlik: Symbolic Likelihood Models in Python

Introducing symlik - define statistical models symbolically and automatically derive score functions, Hessians, and Fisher information.

Likelihood Models for Series Systems with Masked Component Failure Data: An R Package for Maximum Likelihood Estimation

mdrelax: When Masking Conditions Don't Hold

Extending masked failure data analysis when traditional C1-C2-C3 conditions are violated.

Model Selection for Weibull Series Systems: When Simpler Models Suffice

When can reliability engineers safely use simpler models? This paper provides sharp boundaries through likelihood ratio tests on Weibull series systems.

Closed-Form Results for Masked Exponential Series Systems

This paper provides complete analytical results for maximum likelihood estimation in series systems with masked failure data under exponential component lifetimes. Unlike numerical approaches, everything here has a closed form.

The Problem

In series …

Statistical Inference for Series Systems from Masked Failure Time Data: The Exponential Case

Reliability Estimation in Series Systems: Maximum Likelihood Techniques for Right-Censored and Masked Failure Data

Maximum likelihood estimation of component reliability from masked failure data in series systems, with BCa bootstrap confidence intervals validated through extensive simulation studies.

Model Selection for Reliability Estimation in Series Systems

Reliability Estimation in Series Systems: Maximum Likelihood Techniques for Right-Censored and Masked Failure Data

Reliability Estimation in Series Systems Maximum Likelihood Techniques for Right-Censored and Masked Failure Data

dfr.dist: Specify the Hazard Function Directly

Most survival analysis forces you to pick from a catalog—Weibull, exponential, log-normal. dfr.dist flips this: you specify the hazard function directly, and it handles all the math.

The Core Insight

Instead of choosing Weibull(shape, scale), you …

Dynamic failure rate (DFR) distributions

Reliability Analysis and the Problem of Censored Data

One of the most interesting statistical problems I’ve encountered is reliability analysis with censored data—situations where you know something didn’t fail, but not when it will fail.

The Censoring Problem

Imagine testing light bulbs. …