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|Title:||Maximum likelihood estimation of the fractional differencing parameter in an ARFIMA model using wavelets||Authors:||Tse, Y.K.
Fractional differencing parameter
Maximum likelihood estimation
|Issue Date:||2002||Citation:||Tse, Y.K., Anh, V.V., Tieng, Q. (2002). Maximum likelihood estimation of the fractional differencing parameter in an ARFIMA model using wavelets. Mathematics and Computers in Simulation 59 (1-3) : 153-161. ScholarBank@NUS Repository. https://doi.org/10.1016/S0378-4754(01)00403-7||Abstract:||In this paper, we examine the finite-sample properties of the approximate maximum likelihood estimate (MLE) of the fractional differencing parameter d in an ARFIMA(p, d, q) model based on the wavelet coefficients. Ignoring wavelet coefficients of higher order of resolution, the remaining wavelet coefficients approximate a sample of independently and identically distributed normal variates with homogeneous variance within each level. The approximate MLE performs satisfactorily and provides a robust estimate for which the short memory component need not be specified.©2002 IMACS. Published by Elsevier Science B.V. All rights reserved.||Source Title:||Mathematics and Computers in Simulation||URI:||http://scholarbank.nus.edu.sg/handle/10635/19942||ISSN:||03784754||DOI:||10.1016/S0378-4754(01)00403-7|
|Appears in Collections:||Staff Publications|
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