symlik v0.2.0

Features

Thesis Reproduction

• Added examples/thesis_reproduction.py demonstrating 5-component Weibull series system
• Implements Bernoulli masking model satisfying C1/C2/C3 conditions
• Reproduces simulation study from "Reliability Estimation in Series Systems" (Towell, 2023)

Rerum DSL Integration

• Added examples/rerum_integration.py showing DSL-based likelihood modeling
• Added examples/likelihood.rules with reusable rule definitions
• Human-readable format for expressing distribution contributions

Series Systems

• build_weibull_series_contributions() factory function
• Support for known cause, masked cause, and censored observations
• Mixed component types (exponential + Weibull)

Documentation

• New tutorial: Thesis Reproduction
• Comprehensive API reference
• Updated README with all new features

Installation

pip install symlik

Links

• Documentation: https://queelius.github.io/symlik/
• Repository: https://github.com/queelius/symlik