statsmodels

Estimate regression and time-series models for statistical inference.

52|6|Updated Nov 24, 2025

Search Tags:#diagnostics #statistics #regression #time-series #GLM

Ready to run

npx skills add https://github.com/ovachiever/droid-tings --skill statsmodels

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: statsmodels
Source: https://github.com/ovachiever/droid-tings/tree/main/skills/statsmodels
Command: npx skills add https://github.com/ovachiever/droid-tings --skill statsmodels

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

Statsmodels provides extensive statistical modeling tools, diagnostics, and inference methods for regression, time series, GLM, and more.

Core Features & Use Cases

Linear and generalized linear models (OLS, GLS, GLM)
Time series (ARIMA, SARIMAX, Exponential Smoothing)
Hypothesis tests, diagnostics, and model selection
Publication-ready summary statistics and tables

Quick Start

Fit an OLS model, interpret the summary, and generate predictions with confidence intervals.

Frequently Asked Questions about statsmodels

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I fit a regression model and interpret statistical significance?▼

Statsmodels estimates regression models like OLS, WLS, and GLS, then produces publication-ready summaries with p-values, confidence intervals, and diagnostic tests to assess statistical significance and model fit.

Can I use statsmodels for time-series forecasting and ARIMA models?▼

Yes. Statsmodels implements ARIMA, SARIMAX, exponential smoothing, and VAR models for time-series analysis, forecasting, and inference with built-in diagnostics and predictive intervals.

What diagnostic tools does statsmodels provide for model validation?▼

Statsmodels includes hypothesis tests, outlier detection, residual diagnostics, model comparison metrics (AIC/BIC, likelihood ratio tests), and heteroskedasticity checks to validate regression and time-series models.

How do I compare statistical models and select the best one?▼

Statsmodels provides AIC, BIC, and likelihood ratio tests to compare nested and non-nested models, enabling rigorous model selection across linear, GLM, and time-series specifications.

Does statsmodels support generalized linear models and count data?▼

Yes. Statsmodels fits GLM, Poisson, Binomial, Gamma, and count models for classification and regression on non-normal response data with appropriate link functions and dispersion estimates.

Can I generate confidence intervals and prediction intervals from fitted models?▼

Statsmodels computes confidence intervals for parameters and prediction intervals with specified coverage levels for OLS, GLM, time-series, and other model classes for inference and forecasting.