Impact of missing data on the prediction of random fields

Abdelghani Hamaz, Ouerdia Arezki and Farida Achemine

Journal of Applied Statistics, 2020, vol. 47, issue 1, 132-149

Abstract: The purpose of this paper is to treat the prediction problems where a number of observations are missing to the quarter-plane past of a stationary random field. Our aim is to quantify the influence of missing values on the prediction by giving the simple bounds for the prediction error variance. These bounds allow to characterize the random fields for which the missing observations do not affect the prediction. Simulation experiments and an application to real data are presented.

Date: 2020
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Persistent link: https://EconPapers.repec.org/RePEc:taf:japsta:v:47:y:2020:i:1:p:132-149

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DOI: 10.1080/02664763.2019.1633286

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