Linear Time Series Models with Non-Gaussian Innovations

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

Chapter Chapter 6 in Non-Gaussian Autoregressive-Type Time Series, 2021, pp 155-194 from Springer

Abstract: Abstract The time series models with normally distributed innovations generate stationary normal sequences. However, if the innovations are not normal then the stationary marginal distribution may be a member of an entirely different family. This chapter discusses autoregressive models with innovations belonging to various classes of non-Gaussian distributions. Detailed analysis of the models with innovation distributions such as stable, Laplace, heavy-tailed, exponential, gamma, and mixed normal is considered along with the problem of estimation.

Date: 2021
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-981-16-8162-2_6

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DOI: 10.1007/978-981-16-8162-2_6

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