Fit OLS, GLM, logistic, and ARIMA models with statsmodels.
npx skills add https://github.com/robinbarvaag/poynt --skill statsmodels-robinbarvaag
Please help me install this Agent Skill. Skill: statsmodels Source: https://github.com/robinbarvaag/poynt/tree/main/.github/skills/statsmodels Command: npx skills add https://github.com/robinbarvaag/poynt --skill statsmodels-robinbarvaag
This Skill provides a comprehensive toolkit for statistical modeling, enabling rigorous inference and analysis across various domains.
Use the statsmodels skill to fit an OLS model with y as the dependent variable and x1, x2 as independent variables.
High-intent search queries and answers about installing and using this skill.
To perform statistical modeling and hypothesis testing, you can use this toolkit to estimate linear models, generalized linear models, and run advanced diagnostics using R-style formulas for rigorous inference.
Yes, you can fit an OLS regression model using R-style formulas by specifying your dependent and independent variables directly to estimate parameters and generate diagnostic tests.
The best way to forecast time series data is by fitting ARIMA models, which enable you to capture temporal trends, perform statistical inference, and generate predictive forecasts for historical data.
Yes, this toolkit supports econometric modeling by enabling the estimation of discrete choice models, generalized linear models, and running advanced statistical tests for data analysis.
You can build a predictive model for customer churn by applying logistic regression to your historical data, estimating the model parameters, and evaluating statistical significance through hypothesis testing.
dangelesDesign experimental protocols with success criteria, controls, and prioritized experiments.
augustoheissAnalyze raw test results to identify failure patterns, coverage gaps, and release readiness.
tassiovaleFit linear regression and time series models with Python's statsmodels library.
ovachieverEstimate regression and time-series models for statistical inference.
