Long-Range Dependent Curve Time Series
| Autor: | Degui Li, Peter M. Robinson, Han Lin Shang |
|---|---|
| Rok vydání: | 2019 |
| Předmět: |
Statistics and Probability
Long range dependent Functional principal component analysis Series (mathematics) 05 social sciences Process (computing) 01 natural sciences 010104 statistics & probability 0502 economics and business Statistical physics 0101 mathematics Statistics Probability and Uncertainty 050205 econometrics Mathematics |
| Zdroj: | Journal of the American Statistical Association. 115:957-971 |
| ISSN: | 1537-274X 0162-1459 |
| DOI: | 10.1080/01621459.2019.1604362 |
| Popis: | We introduce methods and theory for functional or curve time series with long-range dependence. The temporal sum of the curve process is shown to be asymptotically normally distributed, the conditions for this covering a functional version of fractionally integrated autoregressive moving averages. We also construct an estimate of the long-run covariance function, which we use, via functional principal component analysis, in estimating the orthonormal functions spanning the dominant subspace of the curves. In a semiparametric context, we propose an estimate of the memory parameter and establish its consistency. A Monte Carlo study of finite-sample performance is included, along with two empirical applications. The first of these finds a degree of stability and persistence in intraday stock returns. The second finds similarity in the extent of long memory in incremental age-specific fertility rates across some developed nations. Supplementary materials for this article are available online. |
| Databáze: | OpenAIRE |
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