Quadratic–Inverse Estimates Of Autocorrelation

Abstract

We reconsider the classical problem of estimating the auto-correlation sequence of a stationary time series using quadratic-inverse spectrum estimates. This paper collapses the free-parameter expansion ambiguity of quadratic-inverse spectrum estimates and results in estimates of autocorrelations that have simultaneously low bias and variance.