What data formats are required for input?

The skill requires two CSV files: a price file with datetime and price columns, and an events file with datetime and event descriptions.

Can I adjust the sensitivity of the event window?

Yes, you can configure the event window size (days before and after) using the --window-days parameter during the model configuration step.

Do I need a Nixtla API key to use this modeler?

Yes, a valid NIXTLA_TIMEGPT_API_KEY is required to generate the underlying baseline forecasts used for the causal impact analysis.

What is the primary benefit of using this skill?

It automates the complex process of quantifying how much an external event actually changed your price data compared to a counterfactual scenario where the event never occurred.

What kind of reports does the skill generate?

It produces a comprehensive markdown report, a statistical summary text file, detailed CSV results, and a PNG visualization showing the treatment effects.

Nixtla Event Impact Modeler

Name: Nixtla Event Impact Modeler
Author: intent-solutions-io

byintent-solutions-io

Ciencia de Datos y ML

Quantifies the causal impact of external events on contract prices using TimeGPT forecasting and Bayesian structural time-series analysis.

Acerca de

The Nixtla Event Impact Modeler is a sophisticated analytical tool that helps developers and data scientists measure how specific interventions—such as promotions, policy shifts, or natural disasters—affect time-series data. By combining Nixtla's TimeGPT forecasting with CausalImpact's MCMC-based counterfactual modeling, it isolates the true effect of an event by comparing actual results against a 'what-if' baseline. This skill automates the entire workflow from data validation and event window configuration to the generation of high-resolution visual reports and detailed statistical summaries.

Características Principales

High-resolution visualizations of actual vs. counterfactual price trends
Comprehensive markdown report generation with statistical summaries
0 GitHub stars
Integration with Nixtla TimeGPT for high-accuracy baseline forecasting
Automated event window configuration and treatment period marking
Causal impact analysis using MCMC-based counterfactual modeling

Casos de Uso

Investigating pricing anomalies by isolating the effects of external market shocks
Assessing the economic impact of natural disasters or policy changes on market contracts
Quantifying the price lift and ROI of promotional marketing campaigns

Acerca de

Características Principales

High-resolution visualizations of actual vs. counterfactual price trends
Comprehensive markdown report generation with statistical summaries
0 GitHub stars
Integration with Nixtla TimeGPT for high-accuracy baseline forecasting
Automated event window configuration and treatment period marking
Causal impact analysis using MCMC-based counterfactual modeling

Casos de Uso

Investigating pricing anomalies by isolating the effects of external market shocks
Assessing the economic impact of natural disasters or policy changes on market contracts
Quantifying the price lift and ROI of promotional marketing campaigns