eprintid: 1883
rev_number: 8
eprint_status: archive
userid: 2
dir: disk0/00/00/18/83
datestamp: 2017-02-08 13:07:18
lastmod: 2018-03-28 12:07:50
status_changed: 2017-02-08 13:07:18
type: article
metadata_visibility: show
creators_name: Kiremidjian, Anne S.
creators_name: Anagnos, Thalia
corp_creators: Department of Civil Engineering Terman Engineering Center Stanford University, Stanford, California, USA
corp_creators: Department of Civil Engineering Terman Engineering Center Stanford University, Stanford, California, USA
title: Stochastic slip-predictable model for earthquake occurrences
subjects: MP2_1
subjects: MP2_2
divisions: EPOS-IP
full_text_status: none
abstract: A slip-predictable stochastic model is presented based on Markov renewal theory. Times between successive events are assumed to be Weibull-distributed with an increasing hazard rate. The model forecasts probabilities of earthquake occurrences conditional on the time of occurrence of the last event. The hazard along the Middle America Trench, Mexico, where data has suggested slip-predictable behavior, is obtained for illustrative purposes. Comparisons of this model with the Poisson model show that probability forecasts are underestimated with the Poisson model when there has been a seismic gap. The slip-predictable stochastic model presented in this paper represents a considerable improvement over the existing seismic hazard analysis methods. However, further testing of the model is necessary prior to wider application.
date: 1984-04
date_type: published
publication: Bulletin of the Seismological Society of America
volume: 74
number: 2
publisher: Seismological Society of America
pagerange: 739-755
issn: 0037-1106
official_url: http://www.bssaonline.org/content/74/2/739.abstract
access_IS-EPOS: limited
software_references: Stationarity_test
owner: Publisher
citation:   Kiremidjian, Anne S. and Anagnos, Thalia  (1984) Stochastic slip-predictable model for earthquake occurrences.  Bulletin of the Seismological Society of America, 74 (2).  pp. 739-755.