Loss modelling framework.
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Updated
Jul 17, 2026 - Python
Loss modelling framework.
A repository for modelling and analysing multi-degree-of-freedom systems for response characterisation of global building classes
A Python command-line utility for Linux that computes the economic loss for hurricanes in Florida and in the Gulf states
File validation and data sampling toolkit for the Simplitium Open Exposure Data (OED) (re)insurance exposure data format
Location-level Florida hurricane catastrophe model in Python: HURDAT2-calibrated hazard + physical wind field (Holland, Vickery-Wadhera, Kaplan-DeMaria), synthetic exposure, HAZUS-anchored vulnerability, OED/YLT/ELT formats, XoL reinsurance with reinstatements, gross/net AEP/OEP curves & PMLs, historical backtesting (Andrew, Ian).
Final Project for Leiden University Media Technology MSc. involving an advanced processing sketch that simulates the effect of catastrophe types on Faraday Wave pattern morphology during audiovisual playback. All code by Trent Eriksen and inspired by research from Amber van der Tuin
Compatibility-first R pipeline for cross-country earthquake damage modelling. Harmonises asset-level building-damage data from Nepal (2015 Gorkha), Türkiye (2023) and Japan (2024 Noto), benchmarks within-country models, runs Nepal–Türkiye transfer, and isolates compatibility vs. classifier effects via simulation.
Monte Carlo simulation modelling flood-related financial losses in South Africa using probabilistic risk analysis.
Eradicate all the silliness this year has given us ⚡
Monte Carlo catastrophe risk model using NOAA HURDAT2 Atlantic hurricane data to estimate Expected Annual Loss (EAL), exceedance probabilities, and tail risk.
This repo serves as a guide for understanding what extreme value theory is, using the genextreme package.
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