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    ESTIMATION OF MISSING VALUES FOR BILINEAR TIME SERIES MODELS WITH GARCH INNOVATIONS USING NONPARAMETRIC METHODS

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    Date
    2016
    Author
    ABAJA, POTI OWILI
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    Abstract
    A 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 Imputation is a necessary part of preprocessing of time series data
    URI
    http://ir.kabarak.ac.ke/handle/123456789/721
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    • 6th Annual Conference Kabarak University 2016 [83]

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