td-arimaestimate

What problem does it solve?

This Skill automates the complex process of identifying and estimating the optimal parameters for ARIMA (AutoRegressive Integrated Moving Average) models, crucial for accurate time series forecasting.

Core Features & Use Cases

• Automated Parameter Estimation: Automatically determines the best (p, d, q) and seasonal (P, D, Q, s) orders for ARIMA models.
• Model Diagnostics: Provides comprehensive analysis of model fit, residual diagnostics, and autocorrelation to ensure model adequacy.
• Use Case: Forecast future sales figures by first using this Skill to build a robust ARIMA model based on historical sales data, ensuring the model accurately captures trends and seasonality.

Quick Start

Use the td-arimaestimate skill to analyze the time series table 'my_database.sales_data' with timestamp column 'sale_date' and value column 'units_sold'.