Time series: theory and methods
Time series: theory and methods
ICOSCO-I conference proceedings on The frontiers of statistical scientific theory & industrial applications (Vol. II)
Space-time variograms and a functional form for total air pollution measurements
Computational Statistics & Data Analysis
A local space-time kriging approach applied to a national outpatient malaria data set
Computers & Geosciences
FORTRAN programs for space-time multivariate modeling and prediction
Computers & Geosciences
Towards an automatic procedure for modeling multivariate space-time data
Computers & Geosciences
Predicting spatio-temporal random fields: Some computational aspects
Computers & Geosciences
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Modified GSLIB FORTRAN 77 routines are given in this paper for estimating and modeling space-time variograms. Two general families of models are incorporated in the programs: these are the product model and the product-sum model, both based on the decomposition of the space-time covariance in terms of a space covariance and a time covariance. The GSLIB kriging program has also been modified to incorporate these space-time models. One of the programs detects and removes temporal periodicities in the data. The program removes them and generates residuals for all monitoring stations, in order to estimate and model the spatial-temporal variogram using residuals. The modified kriging program also allows the use of cross-validation in conjunction with fitting of space-time variogram models. The trend component and the residual variogram model can be used for prediction. To illustrate the use of the programs, hourly averages of NO2 for the first ten months of 1998 in Lombardy were used.