A stable estimator of the information matrix under EM for dependent data

Please use this identifier to cite or link to this item: https://doi.org/10.1007/s11222-009-9149-4

Title:	A stable estimator of the information matrix under EM for dependent data
Authors:	Duan, J.-C. Fulop, A.
Keywords:	EM GARCH Information matrix Kalman filter Maximum likelihood Particle filter
Issue Date:	2011
Citation:	Duan, J.-C., Fulop, A. (2011). A stable estimator of the information matrix under EM for dependent data. Statistics and Computing 21 (1) : 83-91. ScholarBank@NUS Repository. https://doi.org/10.1007/s11222-009-9149-4
Abstract:	This article develops a new and stable estimator for information matrix when the EM algorithm is used in maximum likelihood estimation. This estimator is constructed using the smoothed individual complete-data scores that are readily available from running the EM algorithm. The method works for dependent data sets and when the expectation step is an irregular function of the conditioning parameters. In comparison to the approach of Louis (J. R. Stat. Soc., Ser. B 44:226-233, 1982), this new estimator is more stable and easier to implement. Both real and simulated data are used to demonstrate the use of this new estimator. © 2009 Springer Science+Business Media, LLC.
Source Title:	Statistics and Computing
URI:	http://scholarbank.nus.edu.sg/handle/10635/44418
ISSN:	09603174
DOI:	10.1007/s11222-009-9149-4
Appears in Collections:	Staff Publications

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