Estimation of harmonic component in regression with cyclically dependent errors

TL;DR

This paper investigates methods for accurately estimating hidden periodic signals in non-linear regression models affected by cyclically dependent stationary noise, establishing the statistical properties of the estimators.

Contribution

It introduces new theoretical results on the consistency and asymptotic normality of least-squares estimates in models with cyclical dependence.

Findings

Least-squares estimates are consistent.

Estimates are asymptotically normal.

Applicable to models with cyclical dependence in noise.

Abstract

This paper deals with the estimation of hidden periodicities in a non-linear regression model with stationary noise displaying cyclical dependence. Consistency and asymptotic normality are established for the least-squares estimates.