A Note on the Asymptotic Behavior of the LSE's of the Parameters for Superimposed Exponential Signals in Presence of Stationary Noise

Abstract

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.

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Document Details

Document Type
Technical Report
Publication Date
May 07, 1999
Accession Number
ADA364413

Entities

People

  • Debasis Kundu
  • Rameshwar D. Gupta

Organizations

  • Pennsylvania State University

Tags

Communities of Interest

  • C4I
  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Asymptotic Normality
  • Covariance
  • Data Science
  • Estimators
  • Frequency
  • Information Processing
  • Information Science
  • Knowledge Management
  • Mathematics
  • Network Science
  • Normal Distribution
  • Probability
  • Random Variables
  • Signal Processing
  • Statistical Algorithms
  • Statistics
  • Stochastic Processes

Fields of Study

  • Mathematics

Readers

  • Statistical inference.