Modeling marked point processes using bivariate mixture transition distribution models

Mohamed Yusuf Hassan; Keh Shin Lii

doi:10.1109/HOST.1999.778744

Modeling marked point processes using bivariate mixture transition distribution models

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

We propose new statistical models for the analysis of marked point processes. These models deal with data that arrives in unequal intervals, such as financial transactions or heart attacks. The models treat both the time between event arrivals and the observed marks as stochastic processes. We propose and investigate a class of bivariate distributions to form the bivariate mixture transition distribution (BMTD). In these models the bivariate conditional distribution of the next observation given the past is a mixture of conditional distributions given each one of the last k observations. The identifiability of the model is investigated, and the EM algorithm is developed to obtain estimates of the model parameters.

Original language	English
Title of host publication	Proceedings of the IEEE Signal Processing Workshop on Higher-Order Statistics, SPW-HOS 1999
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	285-289
Number of pages	5
ISBN (Electronic)	0769501400, 9780769501406
DOIs	https://doi.org/10.1109/HOST.1999.778744
Publication status	Published - 1999
Externally published	Yes
Event	1999 IEEE Signal Processing Workshop on Higher-Order Statistics, SPW-HOS 1999 - Caesarea, Israel Duration: Jun 14 1999 → Jun 16 1999

Publication series

Name	Proceedings of the IEEE Signal Processing Workshop on Higher-Order Statistics, SPW-HOS 1999

Other

Other	1999 IEEE Signal Processing Workshop on Higher-Order Statistics, SPW-HOS 1999
Country/Territory	Israel
City	Caesarea
Period	6/14/99 → 6/16/99

ASJC Scopus subject areas

Signal Processing
Statistics and Probability

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10.1109/HOST.1999.778744

Cite this

Hassan, M. Y., & Lii, K. S. (1999). Modeling marked point processes using bivariate mixture transition distribution models. In Proceedings of the IEEE Signal Processing Workshop on Higher-Order Statistics, SPW-HOS 1999 (pp. 285-289). Article 778744 (Proceedings of the IEEE Signal Processing Workshop on Higher-Order Statistics, SPW-HOS 1999). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/HOST.1999.778744

Modeling marked point processes using bivariate mixture transition distribution models. / Hassan, Mohamed Yusuf; Lii, Keh Shin.
Proceedings of the IEEE Signal Processing Workshop on Higher-Order Statistics, SPW-HOS 1999. Institute of Electrical and Electronics Engineers Inc., 1999. p. 285-289 778744 (Proceedings of the IEEE Signal Processing Workshop on Higher-Order Statistics, SPW-HOS 1999).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Hassan, MY & Lii, KS 1999, Modeling marked point processes using bivariate mixture transition distribution models. in Proceedings of the IEEE Signal Processing Workshop on Higher-Order Statistics, SPW-HOS 1999., 778744, Proceedings of the IEEE Signal Processing Workshop on Higher-Order Statistics, SPW-HOS 1999, Institute of Electrical and Electronics Engineers Inc., pp. 285-289, 1999 IEEE Signal Processing Workshop on Higher-Order Statistics, SPW-HOS 1999, Caesarea, Israel, 6/14/99. https://doi.org/10.1109/HOST.1999.778744

Hassan MY, Lii KS. Modeling marked point processes using bivariate mixture transition distribution models. In Proceedings of the IEEE Signal Processing Workshop on Higher-Order Statistics, SPW-HOS 1999. Institute of Electrical and Electronics Engineers Inc. 1999. p. 285-289. 778744. (Proceedings of the IEEE Signal Processing Workshop on Higher-Order Statistics, SPW-HOS 1999). doi: 10.1109/HOST.1999.778744

Hassan, Mohamed Yusuf ; Lii, Keh Shin. / Modeling marked point processes using bivariate mixture transition distribution models. Proceedings of the IEEE Signal Processing Workshop on Higher-Order Statistics, SPW-HOS 1999. Institute of Electrical and Electronics Engineers Inc., 1999. pp. 285-289 (Proceedings of the IEEE Signal Processing Workshop on Higher-Order Statistics, SPW-HOS 1999).

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Modeling marked point processes using bivariate mixture transition distribution models

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