[Claude] Add user guide on resampling-free quantile bootstrap#29
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Documents the Schultzberg & Ankargren (2022) recipe for bootstrap inference on sample quantiles at large n: sort once, draw indices from Bin(n+1, q), look up order statistics, feed the resulting theta_star into the existing percentile_interval API. The library already exposes the composable hook (theta_star= argument) so no new code is required; this guide explains when and how to use it. https://claude.ai/code/session_01CRkE1qgfLrZz9oxcfA2Msu
The deploy_docs.yml workflow now builds the docs in CI and rsyncs docs/_build/html/ to the droplet over SSH, rather than SSHing in and running git pull. docs/_build/ is gitignored, so contributors edit RST sources, commit, and push — CI handles the rest. Drop the obsolete "commit build artifacts" recipe and the stale nginx-proxy-submodule paragraph. https://claude.ai/code/session_01CRkE1qgfLrZz9oxcfA2Msu
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Documents the Schultzberg & Ankargren (2022) recipe for bootstrap
inference on sample quantiles at large n: sort once, draw indices
from Bin(n+1, q), look up order statistics, feed the resulting
theta_star into the existing percentile_interval API. The library
already exposes the composable hook (theta_star= argument) so no
new code is required; this guide explains when and how to use it.
https://claude.ai/code/session_01CRkE1qgfLrZz9oxcfA2Msu