Efficiency of Nonparametric Estimators for Missing Observations of Bilinear Time Series with Gaussian Innovation

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dc.contributor.authorOWILI ABAJA, POTI
dc.contributor.authorNassiuma, Dankt
dc.contributor.authorOrawo, Dr Luke
dc.date.accessioned2021-10-29T07:58:09Z
dc.date.available2021-10-29T07:58:09Z
dc.date.issued2016
dc.description.abstractA time series is defined as data recorded sequentially over a specified period. Since the data are records taken overtime, missing observations in time series are very common. They may occur as a result of lost records, deletion of outliers, calender effects and defective measuring instruments Being unable to account for missing data has several limitations: A severe miss-representation of the phenomenon under studyen_US
dc.identifier.urihttp://ir.kabarak.ac.ke/handle/123456789/722
dc.language.isoenen_US
dc.publisherKabarak Universityen_US
dc.subjectNonparametric Estimatorsen_US
dc.subjectBilinear Time Seriesen_US
dc.titleEfficiency of Nonparametric Estimators for Missing Observations of Bilinear Time Series with Gaussian Innovationen_US
dc.typePresentationen_US

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6th Annual Conference Kabarak University 2016