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University of Illinois at Urbana-Champaign
Exact Maximum Likelihood Estimation of the Kalman Filter Model
Abstract
dc:descriptionThe interpretation of the Kalman filter model (KFM) used in this thesis is one where the transition equation allows the coefficients of a regression equation to follow an autoregressive-moving average process. Thus the KFM is a generalization of the random coefficients model.
Degree
thesis:*- Name thesis:degree_name
- Ph.D.
- Level thesis:degree_level
- Dissertation
- Discipline thesis:degree_discipline
- Economics
- Grantor
- University of Illinois at Urbana-Champaign
- Year dc:date
- 2014
Author and committee
dc:creator, dc:contributor.*- Author dc:creator
-
- Bos, Theodore
Subjects
dc:subject × 1Identifiers
dc:identifier.*- Identifier
- (UMI)AAI8302812
- OAI identifier oai:identifier
- oai:www.ideals.illinois.edu:2142/70728