AUB ScholarWorks
Maximum likelihood based techniques in identifying ARMA models - by Michel Riad Nehme
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| dc.contributor.author | Nehme, Michel Riad |
| dc.date.accessioned | 2012-06-13T07:09:04Z |
| dc.date.available | 2012-06-13T07:09:04Z |
| dc.date.issued | 2005 |
| dc.identifier.uri | http://hdl.handle.net/10938/6982 |
| dc.description | Thesis (M.S.)--Dept. of Mathematics, AUB, 2005.;"Advisor: Dr. John Haddad, Associate Professor, Mathematics--Member of Committee: Dr. Bassam Shayya, Associate Professor, Mathematics--Member of Committee: Dr. Nabil Nassif, Professor, Mathematics" |
| dc.description | Bibliography: leaves 54-55. |
| dc.description.abstract | The aim of this thesis is to investigate some preliminary identification techniq ues in time series Autoregressive Moving Average, ARMA, models. In particular, w e take a look at the sample auto- correlation estimate as the primary identifica tion quantit |
| dc.format.extent | x, 55 leaves : ill. 30 cm. |
| dc.language.iso | eng |
| dc.relation.ispartof | Theses, Dissertations, and Projects |
| dc.subject.classification | T:004537 AUBNO |
| dc.subject.lcsh | Time-series analysis |
| dc.subject.lcsh | Box-Jenkins forecasting |
| dc.title | Maximum likelihood based techniques in identifying ARMA models - by Michel Riad Nehme |
| dc.type | Thesis |
| dc.contributor.department | American University of Beirut. Faculty of Arts and Sciences. Department of Mathematics |
