caa a22 4500 605519498 CHVBK 20210128100730.0 cr unu---uuuuu 210128e20150301xx s 000 0 eng 10.1007/s11009-013-9329-8 doi (NATIONALLICENCE)springer-10.1007/s11009-013-9329-8 Maximum-Likelihood Asymptotic Inference for Autoregressive Hilbertian Processes [Elektronische Daten] ML for Autoregressive Hilbertian Processes [M. Ruiz-Medina, R. Espejo] 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. Springer Science+Business Media New York, 2013 Autoregressive Hilbertian processes nationallicence Central limit results nationallicence EMalgorithm nationallicence Financial data nationallicence Maximum likelihood estimation nationallicence Missing functional data nationallicence Numerical projection methods nationallicence Ruiz-Medina M. Department of Statistics and Operations Research, Faculty of Sciences, University of Granada, Campus Fuente Nueva s/n, 18071, Granada, Spain aut Espejo R. Faculty of Sciences, University of Granada, Campus Fuente Nueva s/n, 18071, Granada, Spain aut Methodology and Computing in Applied Probability Springer US; http://www.springer-ny.com 17/1(2015-03-01), 207-222 1387-5841 17:1<207 2015 17 11009 https://doi.org/10.1007/s11009-013-9329-8 text/html Onlinezugriff via DOI BK010053 XK010053 XK010000 Metadata rights reserved Springer special CC-BY-NC licence nationallicence 1 research-article jats NATIONALLICENCE NATIONALLICENCE NL-springer NATIONALLICENCE 856 40 https://doi.org/10.1007/s11009-013-9329-8 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Ruiz-Medina M. Department of Statistics and Operations Research, Faculty of Sciences, University of Granada, Campus Fuente Nueva s/n, 18071, Granada, Spain aut NATIONALLICENCE 700 1- Espejo R. Faculty of Sciences, University of Granada, Campus Fuente Nueva s/n, 18071, Granada, Spain aut NATIONALLICENCE 773 0- Methodology and Computing in Applied Probability Springer US; http://www.springer-ny.com 17/1(2015-03-01), 207-222 1387-5841 17:1<207 2015 17 11009