Asymptotic inference for multiplicative counting processes based on one realization

Åke Svensson

Journal of Multivariate Analysis, 1990, vol. 33, issue 1, 125-142

Abstract: It is assumed that we observe one realization of an r dimensional counting process with intensities that are products of predictable and observable weight processes, a common function of time, and predictable functions that depend on an unknown parameter [theta]. Given that the realization brings increasing information on [theta] as the observed time grows asymptotic results are proved for the distributions of parameter estimates, certain test statistics for parametric hypothesis, and goodness-of-fit tests.

Keywords: counting; processes; Cox; regression; model; goodness-of-fit; tests; martingale; limit; theorems (search for similar items in EconPapers)
Date: 1990
References: Add references at CitEc
Citations:

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/0047-259X(90)90009-7
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:jmvana:v:33:y:1990:i:1:p:125-142

Ordering information: This journal article can be ordered from
http://www.elsevier.com/wps/find/supportfaq.cws_home/regional
https://shop.elsevie ... _01_ooc_1&version=01

Access Statistics for this article

Journal of Multivariate Analysis is currently edited by de Leeuw, J.

More articles in Journal of Multivariate Analysis from Elsevier
Bibliographic data for series maintained by Catherine Liu ().