Anofox Statistics

What is Anofox Statistics?

Anofox Statistics brings professional-grade statistical analysis directly to DuckDB. Build predictive models, run hypothesis tests, and validate assumptions using pure SQL - no Python overhead, no data export/import cycles.

Key Features

• Regression Analysis - OLS, Ridge, WLS, RLS, Elastic Net with full inference
• Hypothesis Testing - 30+ tests including t-test, ANOVA, chi-square, correlation
• Model Diagnostics - VIF, residual analysis, normality tests, information criteria
• Specialized Models - Poisson GLM, ALM (24 distributions), constrained optimization
• Aggregates & Windows - GROUP BY and OVER patterns for rolling/expanding analysis

Quick Links

Documentation	Description
Installation	Setup and prerequisites
Function Finder	Find the right function for your task
Regression	OLS, Ridge, WLS, RLS, Elastic Net, GLM, ALM, BLS, NNLS
Demand Analysis	AID classification and anomaly detection
Hypothesis Tests	Parametric, nonparametric, correlation
Diagnostics	VIF, residuals, normality, model selection
DuckDB Patterns	Aggregates, windows, helpers

Basic Usage

-- Load the extension
LOAD anofox_statistics;

-- Fit a linear regression model
SELECT
    (model).coefficients,
    (model).r_squared,
    (model).p_values
FROM (
    SELECT anofox_stats_ols_fit_agg(
        revenue,
        [marketing_spend, team_size]
    ) as model
    FROM sales_data
);

This returns coefficients with statistical significance tests, goodness-of-fit metrics, and standard errors - all computed in-database.