Summary
LinearRegression is RTTA's streaming implementation of: Rolling least-squares fitted value.
Update API
result = rtta.LinearRegression().update(value)
The update(...) call consumes one observation using value. advance(...)
uses the same inputs when the caller wants to update state without materializing
a Python return value.
Theory Of Operation
LinearRegression keeps rolling sufficient statistics for the requested statistical quantity. Each update inserts the newest sample, removes any expired sample, and recomputes the current statistic from those maintained sums.
Recurrence
Let \(z_t = value_t\) denote the observation consumed by one
update(...) call and let \(\theta\) denote constructor parameters such as
window lengths, thresholds, and smoothing constants.
update(...) returns a result struct with fields value, slope, intercept, angle, tsf.
Implementation Notes
The recurrence is implemented in src/rtta/indicator.cpp in class LinearRegression.