probability-inference

What problem does it solve?

This Skill addresses the need for robust probability inference in quantitative research, ensuring that models accurately reflect distribution assumptions and account for tail-event realism.

Core Features & Use Cases

• Reproducible Research: Ensures that probability inference workflows are executed with reproducible research practices.
• Parameter Estimation & Validation: Facilitates the estimation of parameters with reproducible calibration settings and thorough validation of model behavior.
• Risk Control: Implements essential risk controls, including parameter bounds, convergence safeguards, and monitoring for drift.
• Use Case: A quantitative analyst needs to build a new risk model that accounts for extreme market events. This Skill can be used to define the model's assumptions, estimate parameters, validate its stability, and ensure it meets strict release criteria.

Quick Start

Use the probability-inference skill to run diagnostics on the input data file 'market_data.csv'.