Estimate regression and time-series models for statistical inference.
npx skills add https://github.com/ovachiever/droid-tings --skill statsmodels
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
Statsmodels provides extensive statistical modeling tools, diagnostics, and inference methods for regression, time series, GLM, and more.
Fit an OLS model, interpret the summary, and generate predictions with confidence intervals.
High-intent search queries and answers about installing and using this skill.
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.
Yes. Statsmodels implements ARIMA, SARIMAX, exponential smoothing, and VAR models for time-series analysis, forecasting, and inference with built-in diagnostics and predictive intervals.
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.
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.
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.
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.
PaneriVatsalAnalyze missing values in CSV datasets and recommend imputation strategies.
jasrajtulsiFit statistical models and run diagnostics in Python with statsmodels.
jkitchinSelect and apply Matplotlib, Seaborn, or Plotly for Python visualizations.
RamanEbrahimiPerform statistical modeling and econometric analysis with OLS, GLM, ARIMA, and more.
