Biases of correlograms and of AR representations of stationary series

• We derive the relation between the biases of correlograms and of estimates of auto-regressive AR(k) representations of stationary series, and we illustrate it with a simple AR example. The new relation allows for k to vary with the sample size, which is a representation that can be used for most stationary processes. As a result, the biases of the estimators of such processes can now be quantified explicitly and in a unified way.

Keyword

Auto-correlation function (ACF) and correlogram

auto-regressive (AR) representation

least-squares bias

Statistics

Statistik

Publication and Content Type

ref (subject category)

art (subject category)