bootstrap
A nonparametric method for statistical inference based on resampling with replacement. It does not rely on assumptions of normality and is applicable to data from a wide variety of distributions.
Timeline (last 90 days)
For binary correct/incorrect results, confidence intervals for accuracy can be estimated using the Wilson interval or bootstrap resampling.
The safety stock formula assumes demand is approximately normal and independent, but actual demand is often intermittent, trending, or seasonal, in which case more robust methods such as bootstrap or quantile regression should be used.
The workspace generation must come from the bootstrap rather than the agent; otherwise the agent can rewrite attempt history and cause the gate to endorse a fabricated story
All Facts (3)
For binary correct/incorrect results, confidence intervals for accuracy can be estimated using the Wilson interval or bootstrap resampling.
50%UnverifiedThe safety stock formula assumes demand is approximately normal and independent, but actual demand is often intermittent, trending, or seasonal, in which case more robust methods such as bootstrap or quantile regression should be used.
50%UnverifiedThe workspace generation must come from the bootstrap rather than the agent; otherwise the agent can rewrite attempt history and cause the gate to endorse a fabricated story
50%