Long Memory Models
Long Memory Models is a class of stochastic time series models characterized by a slowly decaying autocorrelation function that captures persistent dependencies over long lags, distinguishing it from short-memory models by exhibiting non-summable correlations indicative of fractional integration in the data-generating process.
1.5K
Publications
215.2K
Citations
2.4K
Authors
1.3K
Institutions
Publications per year
2017–2026
350
1.5K
1–5 of 1.5K
2.4K
28
h-index
London School of Economics and Political Science, United Kingdom
25 publications · 2.3K citations
20
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18
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16
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London School of Economics and Political Science, United Kingdom
17 publications · 1.2K citations
15
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1–5 of 2.4K
1.3K
Universidad de Navarra
Pamplona, Spain
27 h-index
68 publications
2.5K citations
Michigan State University
East Lansing, United States
23 h-index
45 publications
5.5K citations
London School of Economics and Political Science
London, United Kingdom
21 h-index
37 publications
2.7K citations

Centre National de la Recherche Scientifique
Paris, France
21 h-index
62 publications
3.8K citations
New York University
New York, United States
17 h-index
34 publications
3K citations

Aarhus University
Aarhus, Denmark
17 h-index
45 publications
2.2K citations

Vilnius University
Vilnius, Lithuania
16 h-index
31 publications
1.2K citations

Brunel University of London
London, United Kingdom
15 h-index
20 publications
734 citations
1–8 of 1.3K
42 publications · 8.9K citations
31
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51 publications · 9.5K citations
30
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44 publications · 2.1K citations
27
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Repository · 65 publications · 2.3K citations
26
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JBES · 24 publications · 3.1K citations
20
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