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In particular, we consider how to take decision regarding fault detection in a noisy environment as a result of false detection or false response of event by some sensors, where the sensors are placed at the center of regular hexagons and the event can occur at only one hexagon. We propose fault detection schemes that explicitly introduce the error probabilities into the optimal event detection process. We introduce two types of detection probabilities, one for the center node, where the event occurs, and the other one for the adjacent nodes. This second type of detection probability is new in sensor network literature. We develop schemes under the model selection procedure and multiple model selection procedure and use the concept of Bayesian model averaging to identify a set of likely fault sensors and obtain an average predictive error. <\/jats:p>","DOI":"10.1155\/2014\/148234","type":"journal-article","created":{"date-parts":[[2014,1,20]],"date-time":"2014-01-20T21:02:22Z","timestamp":1390251742000},"page":"148234","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":6,"title":["Model Selection Approach for Distributed Fault Detection in Wireless Sensor Networks"],"prefix":"10.1177","volume":"10","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0651-7935","authenticated-orcid":false,"given":"Mrinal","family":"Nandi","sequence":"first","affiliation":[{"name":"Department of Statistics, West Bengal State University, Barasat, India"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Anup","family":"Dewanji","sequence":"additional","affiliation":[{"name":"ASD, Indian Statistical Institute, 203 B. 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