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dc.creatorSter , David
dc.creatorOng’ala, Jacob Otieno
dc.creatorStern, Roger
dc.dateWed, 7 Nov 2012 17:06:05
dc.dateWed, 6 Feb 2013 10:34:47
dc.date.accessioned2015-03-18T11:28:45Z
dc.date.available2015-03-18T11:28:45Z
dc.identifier.urihttp://hdl.handle.net/11071/3374
dc.descriptionRainfall is of critical importance for many people particularly those whose livelihoods are dependent on rain fed agriculture. Methods of analysis of daily rainfall records based on Markov chain models have been available for many years and their value is widely recognized. However they are rarely used because of the complexity of their analysis. This paper describes how these models are being made more accessible through a series of specially written procedures and menus in GenStat, a widely available statistics package.
dc.description.abstractRainfall is of critical importance for many people particularly those whose livelihoods are dependent on rain fed agriculture. Methods of analysis of daily rainfall records based on Markov chain models have been available for many years and their value is widely recognized. However they are rarely used because of the complexity of their analysis. This paper describes how these models are being made more accessible through a series of specially written procedures and menus in GenStat, a widely available statistics package.
dc.languageeng
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dc.subjectGenstat
dc.subjectrainfall data
dc.subjectmarkov chain model
dc.titleExtending genstat capability to analyze rainfall data using Markov chain model
dc.typeThesis


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