A four-parameter interrupted time series fit (pre-trend, level change,
slope change) by OLS, with a Bartlett-kernel HAC covariance, the n/(n-k)
small-sample factor and Student t intervals. The tests pin the
coefficients, standard errors and intervals to independently computed
reference values on contiguous and gapped series.
Six readers fitted a line by hand, four in the determinant form that
loses digits on a large x axis, and the two charts carried the same trend
function twice. linearFit / fitFromSums in lib/stats is now the one
implementation (centred sums, so a fit from points and one composed from
stored accumulators are the same arithmetic), trendLineByTime serves both
charts with the same two-decimal output, and a guard keeps hand-rolled
slopes out of the tree.
About a dozen hand-rolled spreads each picked population or sample
variance without saying so, and the two surfaces a person compares
picked differently: the series API reported the population SD of a
blood-pressure series, the MCP tools and the AI payload the sample SD of
the same readings, about 22 % apart at three readings.
`lib/stats/spread` holds `variance` and `standardDeviation` with an
explicit `population | sample` kind and `READING_SPREAD`, the kind every
surface uses to report the spread of a person's readings. The series
route and the feature payload both report it; the spreads that feed a
verdict (the normal-swing checks, the changepoint threshold) and the
clinical glucose SD stay the sample estimate, now said out loud. A guard
fails on a new hand-rolled spread and on the two surfaces drifting apart.
Marc-André Bombeck