Partial likelihood inference for time series following generalized linear models

Fokianos, K. and Kedem, B. (2004) Partial likelihood inference for time series following generalized linear models. Journal of Time Series Analysis, 25 (2). pp. 173-197. ISSN 0143-9782

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Abstract

The present article offers a certain unifying approach to time series regression modelling by combining partial likelihood (PL) inference and generalized linear models. An advantage gained by resorting to PL is that the joint distribution of the response and the covariates is left unspecified, and furthermore, PL allows for temporal or sequential conditional inference with respect to a filtration generated by all that is known to the observer at the time of observation. Two real data examples illustrate the methodology.

Item Type: Journal Article
Journal or Publication Title: Journal of Time Series Analysis
Uncontrolled Keywords: /dk/atira/pure/subjectarea/asjc/1800/1804
Subjects:
Departments: Faculty of Science and Technology > Mathematics and Statistics
ID Code: 127888
Deposited By: ep_importer_pure
Deposited On: 03 Oct 2018 13:06
Refereed?: Yes
Published?: Published
Last Modified: 30 Sep 2019 21:14
URI: https://eprints.lancs.ac.uk/id/eprint/127888

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