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dc.contributor.authorPENA, Daniel
dc.contributor.authorMARAVALL, Agustin
dc.date.accessioned2011-05-09T15:12:50Z
dc.date.available2011-05-09T15:12:50Z
dc.date.issued1991
dc.identifier.citationCommunications In Statistics-Theory And Methods, 1991, 20, 10, 3175-3186
dc.identifier.issn0361-0926
dc.identifier.urihttps://hdl.handle.net/1814/17078
dc.description.abstractThe paper addresses the problem of estimating missing observations in an infinite realization of a linear, possibly nonstationary, stochastic processes when the model is known. The general case of any possible distribution of missing observations in the time series is considered, and analytical expressions for the optimal estimators and their associated mean squared errors are obtained. These expressions involve solely the elements of the inverse or dual autocorrelation function of the series. This optimal estimator -the conditional expectation of the missing observations given the available ones- is equal to the estimator that results from filling the missing values in the series with arbitrary numbers, treating these numbers as additive outliers, and removing with intervention analysis the outlier effects from the invented numbers.
dc.titleInterpolation, Outliers and Inverse Autocorrelations
dc.typeArticle
dc.neeo.contributorPENA|Daniel|aut|
dc.neeo.contributorMARAVALL|Agustin|aut|
dc.identifier.volume20
dc.identifier.startpage3175
dc.identifier.endpage3186
eui.subscribe.skiptrue
dc.identifier.issue10


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