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Time series models with tailed generalized geometric Linnik distribution as Marginals

Mariamma Antony✉

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.

Citations
1
FWCI
0.54
field-weighted impact
References
6
Percentile
63%
vs. same field & year

Cited by 1

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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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