A Note on the Asymptotic Behavior of the LSE's of the Parameters for Superimposed Exponential Signals in Presence of Stationary Noise
PENNSYLVANIA STATE UNIV UNIVERSITY PARK CENTER FOR MULTIVARIATE ANALYSIS
Pagination or Media Count:
Superimposed exponential signals play an important role in Statistical Signal Processing and Time series analysis. In this note, the asymptotic behavior of the least squares estimators of the parameters are obtained in presence of stationary noise for the undamped exponential model. It is well known that this model does not satisfy the sufficient conditions of Jennrich 1969, Wu 1981 or Kundu 1991 for the least squares estimators to be consistent even when the errors are independent and identically distributed random variables with mean zero and finite variance. This paper extends some of the earlier works of Hannan 1971, 1973, Walker 1971, Bai et al. 1991, Rao and Zhao 1993, Kundu 1995 and Kundu and Mitra 1995, 1998 in different ways. Some numerical experiments are performed to observe the small sample behavior of the least squares estimators.
- Statistics and Probability