Statistical Inference for Stationary Linear Time Series

N. Balakrishna ()
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N. Balakrishna: Cochin University of Science and Technology, Department of Statistics

Chapter Chapter 2 in Non-Gaussian Autoregressive-Type Time Series, 2021, pp 19-39 from Springer

Abstract: Abstract This chapter describes various methods of estimation suitable for the time series models studied in the subsequent chapters and summarizes the properties of the resulting estimators. The methods such as maximum likelihood, conditional least squares, generalized method of moments, quasi-likelihood and estimating function methods are discussed in detail. Relevant references are provided for the detailed proofs of the results stated in the chapter.

Date: 2021
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-981-16-8162-2_2

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DOI: 10.1007/978-981-16-8162-2_2

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