Abstract

GIRALDO, Ramón; PACHECO, Óscar  and  OROZCO, Astrid. Geostatistics applied to autorregresive time series: A simulation study. Integración - UIS [online]. 2017, vol.35, n.1, pp.83-102. ISSN 0120-419X.  https://doi.org/10.18273/revint.v35n1-2017006.

Geostatistics can be used as a method for predicting missing data in time series. The procedure is based on estimating the temporal autocorrelation structure by means of the semivariance function, by least squares (classical geostatistics) or maximum likelihood (model-based geostatistics), and posteriorly using Kriging for doing prediction of missing data in the time series. In this work we compare classical and model-based geoestatistics in the context of time series using simulated autorregresive time series.

Keywords : Autocorrelation; Kriging; Prediction; Missing values; Semivariogram; Time series; Variogram.

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