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dc.contributor.authorMuindi, Jacinta W
dc.date.accessioned2024-07-17T05:17:05Z
dc.date.available2024-07-17T05:17:05Z
dc.date.issued2023
dc.identifier.urihttp://erepository.uonbi.ac.ke/handle/11295/165097
dc.description.abstractThis study is on Self-Exciting Threshold Auto regressive (SETAR)modeling of the NSE 20 Share Index using the Bayesian approach.The objectives of the study are toana- lyze the properties o the NSE 20 Share Index data,to determine the estimates of SETAR model parameters using the Bayesian approach,to forecast the NSE 20 Share Index for the next 12 months using the fitted model,and to compare the forecasting performance of the Bayesian SETAR with the frequentist SETAR and ARIMA model...en_US
dc.language.isoenen_US
dc.publisherUniversity of Nairobien_US
dc.rightsAttribution-NonCommercial-NoDerivs 3.0 United States*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/us/*
dc.titleSelf-exciting Threshold Autoregressive Modelling of the NSE20 Share Index Using the Bayesian Approachen_US
dc.typeThesisen_US


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Attribution-NonCommercial-NoDerivs 3.0 United States
Except where otherwise noted, this item's license is described as Attribution-NonCommercial-NoDerivs 3.0 United States