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- W2741783960 abstract "This paper considers estimation of the parameters for fractionally integrated processes with infinite variance innovations introduced by Kokoszka and Taqqu (1995). This is a finite parameter model which exhibits long-range dependence and large fluctuations (heavy-tailed distributions). We introduce two procedures to estimate the di erencing parameter and ARMA coe cients. The first one is the Conditional Sum of Squares (CSS) method and the second is the Minimum Hellinger Distance (MHD) estimator. Monte Carlo experiments are used to evaluate the finite sample performance of the proposed estimators, and compare it to the Markov chains Monte Carlo (MCMC) Whittle approach developed by Ndongo et al. (2010)." @default.
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- W2741783960 date "2015-01-01" @default.
- W2741783960 modified "2023-09-23" @default.
- W2741783960 title "Estimation of Fractional ARIMA Process with Stable Innovations: A" @default.
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