tagged · 6 articles
time-series
- 2026
- 2026
Your bootstrap is lying to you
The ordinary bootstrap assumes your observations are independent. Feed it a time series and it quietly shuffles away the autocorrelation, then hands you a confidence interval too narrow to be true: a nominal 90% interval that covers the truth about half the time. Here is the failure on real numbers, and the block bootstrap that keeps the dependence and tells you most of the truth. - 2026
One earthquake pinned my error bound forever
A seismic stream, a global magnitude bound wrecked by a single mainshock, a windowed bound that heals — and a scoreboard where the headline empirical legs of two papers report zero violations. - 2026
The accumulator that never moved
An adversarial input where round-to-nearest throws away every increment in the same direction while the true sum climbs — and the coin flip that breaks the adversary's one weapon, measured across 20,000 seeds. - 2026
The error analysis everyone cites is for a kernel nobody runs
SCAMP and STUMPY accumulate a mean-centred covariance, not the textbook inner product — and the centred case is structurally different floating-point mathematics, not a special case at mu = 0. - 2026
Thirty-one papers, zero error analyses
A sliding-window inner product updated one product at a time is the streaming similarity engine under motif and anomaly mining — its rounding error grows linearly in stream length, and across thirty-one matrix-profile papers nobody had ever done the forward-error math, or turned the fix into a config knob.