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Academia Sinica, Institute of Statistical Science, Statistica Sinica, 3(21), p. 1115-1144

DOI: 10.5705/ss.2009.186

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Spectral density estimation through a regularized inverse problem

Journal article published in 2008 by Chunfeng Huang, Tailen Hsing, Noel Cressie ORCID
This paper is available in a repository.
This paper is available in a repository.

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Abstract

In the study of stationary processes on the real line, the spectral den- sity function is a parameter of considerable interest. In this paper, we consider a new estimator of the spectral density function obtained by a regularized inversion of estimated covariances. In particular, the data are not required to be observed on a grid and the estimator is not based on the periodogram. For data that are observed on a grid, the estimator is derived in closed from, and the mean squared error of the estimator can be computed. A numerical study is also included to illustrate the methodology. Running title: Spectrum estimation through a regularized inverse problem