Anofox Statistics Batch
AI-ready batch and per-group model fitting for the anofox_statistics DuckDB extension — training thousands of regression models in a single SQL query. Covers the *_fit_predict_by table macros (ols_fit_predict_by, huber_fit_predict_by, ransac_fit_predict_by, theil_sen_fit_predict_by, ridge_fit_predict_by, elasticnet_fit_predict_by, wls_fit_predict_by, rls_fit_predict_by, bls_fit_predict_by, alm_fit_predict_by, poisson_fit_predict_by, binomial_fit_predict_by, logistic_fit_predict_by, negbinom_fit_predict_by, gamma_fit_predict_by, tweedie_fit_predict_by, pls_fit_predict_by, isotonic_fit_predict_by, quantile_fit_predict_by, bayesian_ridge_fit_predict_by, ard_fit_predict_by, passive_aggressive_fit_predict_by, lm_dynamic_fit_predict_by) with split := and order_by :=, the per-group long-table macros <model>_tidy_by and <model>_glance_by (25 models), ols/wls/GLM _augment_by, <model>_partial_residuals_by, <model>_prediction_by (23 models), <model>_effects_by (marginal effects), <model>_rolling_tidy_by (rolling coefficients), ridge/elasticnet/lars_path_by, ridge/elasticnet_cv_by, ridge/elasticnet_nested_cv_by, quantile_process_by, acf_by / pacf_by, kaplan_meier_by, roc/pr/calibration_curve_by and pairwise_t_test_by / tukey_hsd_by / dunn_test_by, per-group aggregate fitting with GROUP BY plus predict / tidy / glance on the per-group model structs, the *_fit_predict_agg aggregates, rolling *_fit_predict window functions, the glmm_fit_by / eb_shrink_by / aid_by macros, and scaling patterns for fitting a separate model per segment / SKU / cohort over large panels. Also glmm_tidy_by / glance_by / augment_by, ols_anova_by, mediation_by, p_adjust_by, ridge / elasticnet_nested_cv_by, the split := rule and order_by := for rls_tidy_by. Use when the task is "fit one model per group" at scale, or "give me a coefficient / fit / residual / prediction table per group", rather than a single global fit.
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From the source SKILL.md
Extension: anofox_statistics v0.13.0 | DuckDB: v1.5.6 / v2.0
What this skill does
Anofox Statistics Batch is a community-contributed Claude Code skill in the math-stats sub-category. It ships as a SKILL.md file that Claude Code auto-discovers under ~/.claude/skills/anofox-statistics-batch/ and loads when your prompt matches the skill's trigger.
When to invoke it: Use when the task is "fit one model per group" at scale, or "give me a coefficient / fit / residual / prediction table per group", rather than a single global fit.
Who uses this skill
The Anofox Statistics Batch Claude Code skill is built for researchers, data scientists, academics, and analysts working with complex data and scientific literature. It's part of ClaudSkills (also referred to as Claude Skills or Claude Code Skills) — the open community-curated registry of 211,000+ SKILL.md files for Anthropic's Claude Code agent and the wider Claude ecosystem (Claude API, Claude Agent SDK).
How to install
Free
Manual install (2 steps)
mkdir -p ~/.claude/skills/anofox-statistics-batch
curl -L https://claudskills.com/skills/anofox-statistics-batch/SKILL.md \
-o ~/.claude/skills/anofox-statistics-batch/SKILL.md
Or just download SKILL.md directly and drop it into ~/.claude/skills/anofox-statistics-batch/. Claude Code auto-discovers it on next session.
Skills live at ~/.claude/skills/anofox-statistics-batch/SKILL.md on macOS/Linux, or %USERPROFILE%\.claude\skills\anofox-statistics-batch\SKILL.md on Windows. See the full install guide for step-by-step instructions.
Telegram
📱 Install from your phone or desktop Telegram
Open @claudskills_bot on Telegram, tap Open Desktop App, and the desktop app installs this skill for you. Or share the bot link with a colleague — they get the same one-tap install. Learn more →
Pro
One-click install via the desktop app
The ClaudSkills desktop app installs any skill directly into ~/.claude/skills/ with one click — no terminal required. Pro starts at $9/mo or $149 lifetime.
Pro
For the full experience including quality scoring and one-click install features for each skill — upgrade to Pro.
Frequently asked questions
How do I install the Anofox Statistics Batch Claude Code skill?
Install via the ClaudSkills desktop app (one click) or copy
SKILL.md from the source repository to
~/.claude/skills/anofox-statistics-batch/SKILL.md and restart Claude Code. Both flows are detailed at
claudskills.com/install/.
What does the Anofox Statistics Batch skill do?
AI-ready batch and per-group model fitting for the anofox_statistics DuckDB extension — training thousands of regression models in a single SQL query. Covers the *_fit_predict_by table macros (ols_fit_predict_by, huber_fit_predict_by, ransac_fit_predict_by, theil_sen_fit_predict_by, ridge_fit_predict_by, elasticnet_fit_predict_by, wls_fit_predict_by, rls_fit_predict_by, bls_fit_predict_by, alm_fit_predict_by, poisson_fit_predict_by, binomial_fit_predict_by, logistic_fit_predict_by, negbinom_fit_predict_by, gamma_fit_predict_by, tweedie_fit_predict_by, pls_fit_predict_by, isotonic_fit_predict_by, quantile_fit_predict_by, bayesian_ridge_fit_predict_by, ard_fit_predict_by, passive_aggressive_fit_predict_by, lm_dynamic_fit_predict_by) with split := and order_by :=, the per-group long-table macros <model>_tidy_by and <model>_glance_by (25 models), ols/wls/GLM _augment_by, <model>_partial_residuals_by, <model>_prediction_by (23 models), <model>_effects_by (marginal effects), <model>_rolling_tidy_by (rolling coefficients), ridge/elasticnet/lars_path_by, ridge/elasticnet_cv_by, ridge/elasticnet_nested_cv_by, quantile_process_by, acf_by / pacf_by, kaplan_meier_by, roc/pr/calibration_curve_by and pairwise_t_test_by / tukey_hsd_by / dunn_test_by, per-group aggregate fitting with GROUP BY plus predict / tidy / glance on the per-group model structs, the *_fit_predict_agg aggregates, rolling *_fit_predict window functions, the glmm_fit_by / eb_shrink_by / aid_by macros, and scaling patterns for fitting a separate model per segment / SKU / cohort over large panels. Also glmm_tidy_by / glance_by / augment_by, ols_anova_by, mediation_by, p_adjust_by, ridge / elasticnet_nested_cv_by, the split := rule and order_by := for rls_tidy_by. Use when the task is "fit one model per group" at scale, or "give me a coefficient / fit / residual / prediction table per group", rather than a single global fit.
Is this skill free to install?
Yes. ClaudSkills is an open registry — every skill keeps its source repository's license, and manual install via copy is free. ClaudSkills Pro ($9/mo, $79/yr, or $149 one-time) adds one-click install via the desktop app and a multi-signal Quality Score.
When should I use the Anofox Statistics Batch skill?
Use Anofox Statistics Batch when your Claude Code task falls under the Science & Research category — specifically in the math stats area. Claude Code auto-discovers installed skills and invokes the right one based on the task description, so you can also ask Claude directly (e.g. "use Anofox Statistics Batch" or describe the task and let Claude pick). Browse related skills at
/category/science/.
What is a Claude Code skill and how does the Anofox Statistics Batch skill fit in?
A Claude Code skill is a
SKILL.md file that lives under
~/.claude/skills/<name>/ and tells the Claude Code CLI agent how to perform a specific task (instructions, prompts, allowed tools). Skills are auto-discovered at session start. Anofox Statistics Batch is one of 67,000+ skills indexed in the open ClaudSkills catalog, classified under the Science & Research category. Learn more at
/learn/what-is-a-claude-skill/.
Attribution & license
Cite this skill
If you reference this skill in a blog post, paper, or documentation, you can cite it as:
APA
DataZooDE. (2026). Anofox Statistics Batch [Claude Code skill]. ClaudSkills. https://claudskills.com/skills/anofox-statistics-batch/
BibTeX
@misc{anofox-statistics-batch-2026,
author = {DataZooDE},
title = {Anofox Statistics Batch [Claude Code skill]},
year = {2026},
publisher = {ClaudSkills},
url = {https://claudskills.com/skills/anofox-statistics-batch/}
}
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Security scan
Grade A · scanned 2026-10-25 — free static scan against the OWASP Agentic Skills Top 10.
No risk patterns were found in any of the ten OWASP-aligned categories. How grading works ›
- ✓ Prompt injection
- ✓ Data exfiltration
- ✓ Supply chain
- ✓ Reverse shell
- ✓ Credentials
- ✓ Execution
- ✓ Filesystem
- ✓ Persistence
- ✓ Obfuscation
- ✓ Network
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