In this paper, it is proposed to modify autoregressive fractionally integrated moving average (ARFIMA) processes by introducing an additional parameter to comply with the criticism of Hauser et al. (1999) that ARFIMA processes are not appropriate for the estimation of persistence, because of the degenerate behavior of their spectral densities at frequency zero. When fitting these modified ARFIMA processes to the US GNP, it turns out that the estimated spectra are very similar to those obtained with conventional ARFIMA models, indicating that, in this special case, the disadvantage of ARFIMA models cited by Hauser et al. (1999) does not seriously affect the estimation of persistence. However, according to the results of a goodness-of-fit test applied to the estimated spectra, both the ARFIMA models and the modified ARFIMA models seem to overfit the data in the neighborhood of frequency zero.
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Univ Fed Rio Grande do Sul, Math & Stat Inst, 9500 Bento Goncalves Ave, BR-91509900 Porto Alegre, RS, BrazilUniv Fed Rio Grande do Sul, Math & Stat Inst, 9500 Bento Goncalves Ave, BR-91509900 Porto Alegre, RS, Brazil
Pumi, Guilherme
Valk, Marcio
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Univ Fed Rio Grande do Sul, Math & Stat Inst, 9500 Bento Goncalves Ave, BR-91509900 Porto Alegre, RS, BrazilUniv Fed Rio Grande do Sul, Math & Stat Inst, 9500 Bento Goncalves Ave, BR-91509900 Porto Alegre, RS, Brazil
Valk, Marcio
Bisognin, Cleber
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Univ Fed Santa Maria, Dept Estat, Santa Maria, RS, Brazil
Univ Fed Santa Maria, LACESM, Santa Maria, RS, BrazilUniv Fed Rio Grande do Sul, Math & Stat Inst, 9500 Bento Goncalves Ave, BR-91509900 Porto Alegre, RS, Brazil
Bisognin, Cleber
Bayer, Fabio Mariano
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Univ Fed Santa Maria, Dept Estat, Santa Maria, RS, Brazil
Univ Fed Santa Maria, LACESM, Santa Maria, RS, BrazilUniv Fed Rio Grande do Sul, Math & Stat Inst, 9500 Bento Goncalves Ave, BR-91509900 Porto Alegre, RS, Brazil
Bayer, Fabio Mariano
Prass, Taiane Schaedler
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Univ Fed Rio Grande do Sul, Math & Stat Inst, 9500 Bento Goncalves Ave, BR-91509900 Porto Alegre, RS, BrazilUniv Fed Rio Grande do Sul, Math & Stat Inst, 9500 Bento Goncalves Ave, BR-91509900 Porto Alegre, RS, Brazil
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CUNY Bernard M Baruch Coll, Dept Stat & Comp Informat Syst, New York, NY 10010 USACUNY Bernard M Baruch Coll, Dept Stat & Comp Informat Syst, New York, NY 10010 USA
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Univ Hong Kong, Dept Stat & Actuarial Sci, Hong Kong, Hong Kong, Peoples R ChinaUniv Hong Kong, Dept Stat & Actuarial Sci, Hong Kong, Hong Kong, Peoples R China
Li, Guodong
Li, Wai Keung
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Univ Hong Kong, Dept Stat & Actuarial Sci, Hong Kong, Hong Kong, Peoples R ChinaUniv Hong Kong, Dept Stat & Actuarial Sci, Hong Kong, Hong Kong, Peoples R China
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School of Mathematical Sciences, Uni-versiti Sains Malaysia, Pulau Pinang, Malaysia
Department of Mathematics, Al-Hussein Bin Talal University, Ma'an, JordanSchool of Mathematical Sciences, Uni-versiti Sains Malaysia, Pulau Pinang, Malaysia
Al-Gounmeein, Remal Shaher
Ismail, Mohd Tahir
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School of Mathematical Sciences, Uni-versiti Sains Malaysia, Pulau Pinang, MalaysiaSchool of Mathematical Sciences, Uni-versiti Sains Malaysia, Pulau Pinang, Malaysia