Time series models with tailed generalized geometric Linnik distribution as Marginals
Abstract
Tailed distributions are found to be useful in the study of life testing experiments and clinical trials. Tailed forms of type I and type II generalized geometric Linnik distribution and their asymmetric forms are studied in [1]. The usual technique of transferring data to use a Gaussian model fails in certain situations. Hence a number of non-Gaussian autoregressive models have been introduced by various researchers. A first order autoregressive model with tailed type I generalized geometric Linnik distribution is introduced in this paper. It is shown that the process is not time reversible. The model is extended to higher order cases.
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- On Models of Time Series ↗
Mariamma Antony · International Journal of Advanced Research in Science Communication and Technology · 2024
Recently a number of time series models have been constructed and studied for real valued observations using different marginal distributions by several researchers. Many naturally occurring time series observations show a tendency to follow asymmetric and heavy tailed distributions. A review of literature on some heavy tailed models of time series is done in this paper.
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