Estimate and diagnose statistical models using statsmodels APIs.
npx skills add https://github.com/m0at/claudemd --skill statsmodels-m0at
Please help me install this Agent Skill. Skill: statsmodels Source: https://github.com/m0at/claudemd/tree/main/skills/statsmodels Command: npx skills add https://github.com/m0at/claudemd --skill statsmodels-m0at
Statsmodels provides a comprehensive, Python-based toolkit for rigorous statistical modeling, estimation, inference, and diagnostics across a wide range of model families, helping analysts and researchers obtain reliable results without building models from scratch.
Install Statsmodels and run a simple OLS example to fit y ~ X with an intercept and inspect the results.
High-intent search queries and answers about installing and using this skill.
Run OLS regression by fitting y ~ X with an intercept, then apply heteroskedasticity and autocorrelation checks using built-in diagnostic utilities to validate model assumptions and ensure reliable inference.
Use Generalized Linear Models (GLM) to model non-normal outcomes, applying the Formula API for R-style easy specification to estimate parameters and run hypothesis tests across diverse distributions.
Yes, you can fit ARIMA and SARIMAX models for time-series analysis, alongside VAR and state-space models, to forecast temporal data and run diagnostics on residuals.
Yes, it supports discrete choice and counting models including Logit, Probit, Poisson, Negative Binomial, and zero-inflated variants for analyzing categorical decisions and count data.
Use the Formula API to specify statistical models using R-style syntax, enabling rapid definition of regression and GLM relationships between variables without manual matrix construction.
Statsmodels provides comprehensive estimation and inference across diverse model families, reducing the need to build models from scratch, though it requires robust access to core APIs for proper implementation.
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