Maximum-Likelihood Asymptotic Inference for Autoregressive Hilbertian Processes
ML for Autoregressive Hilbertian Processes
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| 024 | 7 | 0 | |a 10.1007/s11009-013-9329-8 |2 doi |
| 035 | |a (NATIONALLICENCE)springer-10.1007/s11009-013-9329-8 | ||
| 245 | 0 | 0 | |a Maximum-Likelihood Asymptotic Inference for Autoregressive Hilbertian Processes |h [Elektronische Daten] |b ML for Autoregressive Hilbertian Processes |c [M. Ruiz-Medina, R. Espejo] |
| 520 | 3 | |a The autoregressive Hilbertian process framework has been introduced in Bosq (2000). This book provides the nonparametric estimation of the autocorrelation and covariance operators of the autoregressive Hilbertian processes. The asymptotic properties of these estimators are also provided. The maximum likelihood approach still remains unexplored. This paper obtains the asymptotic distribution of the maximum likelihood (ML) estimators of the auto-covariance operator of the Hilbert-valued innovation process, and of the autocorrelation operator of a Gaussian autoregressive Hilbertian process of order one. A real data example is analyzed in the financial context for illustration of the performance of the projection maximum likelihood estimation methodology in the context of missing data. | |
| 540 | |a Springer Science+Business Media New York, 2013 | ||
| 690 | 7 | |a Autoregressive Hilbertian processes |2 nationallicence | |
| 690 | 7 | |a Central limit results |2 nationallicence | |
| 690 | 7 | |a EMalgorithm |2 nationallicence | |
| 690 | 7 | |a Financial data |2 nationallicence | |
| 690 | 7 | |a Maximum likelihood estimation |2 nationallicence | |
| 690 | 7 | |a Missing functional data |2 nationallicence | |
| 690 | 7 | |a Numerical projection methods |2 nationallicence | |
| 700 | 1 | |a Ruiz-Medina |D M. |u Department of Statistics and Operations Research, Faculty of Sciences, University of Granada, Campus Fuente Nueva s/n, 18071, Granada, Spain |4 aut | |
| 700 | 1 | |a Espejo |D R. |u Faculty of Sciences, University of Granada, Campus Fuente Nueva s/n, 18071, Granada, Spain |4 aut | |
| 773 | 0 | |t Methodology and Computing in Applied Probability |d Springer US; http://www.springer-ny.com |g 17/1(2015-03-01), 207-222 |x 1387-5841 |q 17:1<207 |1 2015 |2 17 |o 11009 | |
| 856 | 4 | 0 | |u https://doi.org/10.1007/s11009-013-9329-8 |q text/html |z Onlinezugriff via DOI |
| 898 | |a BK010053 |b XK010053 |c XK010000 | ||
| 900 | 7 | |a Metadata rights reserved |b Springer special CC-BY-NC licence |2 nationallicence | |
| 908 | |D 1 |a research-article |2 jats | ||
| 949 | |B NATIONALLICENCE |F NATIONALLICENCE |b NL-springer | ||
| 950 | |B NATIONALLICENCE |P 856 |E 40 |u https://doi.org/10.1007/s11009-013-9329-8 |q text/html |z Onlinezugriff via DOI | ||
| 950 | |B NATIONALLICENCE |P 700 |E 1- |a Ruiz-Medina |D M. |u Department of Statistics and Operations Research, Faculty of Sciences, University of Granada, Campus Fuente Nueva s/n, 18071, Granada, Spain |4 aut | ||
| 950 | |B NATIONALLICENCE |P 700 |E 1- |a Espejo |D R. |u Faculty of Sciences, University of Granada, Campus Fuente Nueva s/n, 18071, Granada, Spain |4 aut | ||
| 950 | |B NATIONALLICENCE |P 773 |E 0- |t Methodology and Computing in Applied Probability |d Springer US; http://www.springer-ny.com |g 17/1(2015-03-01), 207-222 |x 1387-5841 |q 17:1<207 |1 2015 |2 17 |o 11009 | ||