Modelling of fire count data: fire disaster risk in Ghana

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dc.contributor.authorBoadi, C.
dc.contributor.authorHarvey, S.K.
dc.contributor.authorGyeke-dako, A.
dc.date.accessioned2018-09-04T14:45:31Z
dc.date.available2018-09-04T14:45:31Z
dc.date.issued2015-12
dc.description.abstractStochastic dynamics involved in ecological count data require distribution fitting procedures to model and make informed judgments. The study provides empirical research, focused on the provision of an early warning system and a spatial graph that can detect societal fire risks. It offers an opportunity for communities, organizations, risk managers, actuaries and governments to be aware of, and understand fire risks, so that they will increase the direct tackling of the threats posed by fire. Statistical distribution fitting method that best helps identify the stochastic dynamics of fire count data is used. The aim is to provide a fire-prediction model and fire spatial graph for observed fire count data. An empirical probability distribution model is fitted to the fire count data and compared to the theoretical probability distribution of the stochastic process of fire count data. The distribution fitted to the fire frequency count data helps identify the class of models that are exhibited by the fire and provides time leading decisions. The research suggests that fire frequency and loss (fire fatalities) count data in Ghana are best modelled with a Negative Binomial Distribution. The spatial map of observed fire frequency and fatality measured over 5 years (2007–2011) offers in this study a first regional assessment of fire frequency and fire fatality in Ghana.en_US
dc.identifier.otherhttps://doi.org/10.1186/s40064-015-1585-3
dc.identifier.urihttp://ugspace.ug.edu.gh/handle/123456789/23945
dc.language.isoenen_US
dc.publisherSpringerplusen_US
dc.subjectStochasticen_US
dc.subjectEcological dataen_US
dc.subjectDistribution fittingen_US
dc.subjectStatistical distributionen_US
dc.subjectNegative binomialen_US
dc.subjectPoissonen_US
dc.subjectFatalitiesen_US
dc.subjectFire frequencyen_US
dc.titleModelling of fire count data: fire disaster risk in Ghanaen_US
dc.typeArticleen_US

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