Is it suitable for academic research?

Yes, Statsmodels is the standard library for econometric and statistical research in Python, producing detailed summary tables that meet the requirements for scientific publications.

Does it support time series forecasting?

Absolutely. It includes comprehensive tools for univariate and multivariate time series analysis, including ARIMA, SARIMAX, and VAR models, along with stationarity tests like ADF.

Can I use R-style formulas with this skill?

Yes, this skill supports the Statsmodels Formula API, allowing you to specify complex models using the 'y ~ x1 + x2' syntax familiar to R users, including automatic dummy variable encoding.

What kind of model diagnostics does it provide?

It offers extensive tests for model assumptions, including Breusch-Pagan for heteroskedasticity, Durbin-Watson for autocorrelation, and Cook's distance for detecting influential outliers.

What is the difference between Statsmodels and Scikit-learn?

While Scikit-learn focuses primarily on predictive machine learning and pattern recognition, Statsmodels is designed for statistical inference, hypothesis testing, and understanding the underlying relationships between variables.

Statsmodels Statistical Toolkit

Name: Statsmodels Statistical Toolkit
Author: ricable

byricable

•

データサイエンスとML

Provides a comprehensive suite of statistical modeling tools for rigorous inference, hypothesis testing, and econometric analysis in Python.

The Statsmodels skill empowers Claude to perform high-level statistical modeling and econometric analysis using Python's premier statistics library. It enables the fitting of various regression models—including OLS, GLM, and logistic regression—as well as sophisticated time-series analysis with ARIMA and seasonal models. This skill is essential for users needing to conduct formal hypothesis tests, validate model assumptions through diagnostic checks, and produce publication-ready statistical summaries that go beyond simple machine learning predictions to provide deep inferential insights into data relationships.

主な機能

01Discrete choice models for binary, multinomial, and count data outcomes

021 GitHub stars

03Comprehensive time series analysis suite with ARIMA, SARIMAX, and VAR capabilities

04R-style formula API support for intuitive and flexible model specification

05Advanced linear and generalized linear modeling including OLS, GLM, and WLS

06Rigorous statistical diagnostics for heteroskedasticity, normality, and autocorrelation

ユースケース

01Forecasting financial or economic trends using sophisticated time-series modeling

02Estimating causal relationships and conducting econometric research for academic or business reports

03Validating scientific hypotheses through rigorous statistical testing and residual diagnostics

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add ricable/ultimate-ai-agent statsmodels

For use in Claude.ai and ChatGPT

Download Skill