Inference on variance components of autocorrelated sequences in the presence of drift

Abstract

Many statistics techniques rely on the assumption that random variables measured over time have a common mean. In many situations, this assumption is violated, the mean of the observations drifting gradually over time. For a particular modeling situation, motivated by a psychological study of human rhythm and motor control, a testing procedure for the presence of drift is derived, along with consistent estimators for the variance components. These procedures are applied to a long-run sequence of tapping data.

Keywords:

• Pseudoresiduals
• m-Dependent Data
• Slowly Varying Functions
• Tapping Data