Space-time processes constitute a particular class, requiring suitable tools in order to predict values in time and space, such as a space-time variogram or covariance function. The space-time covariance function is defined and linked to the Linear Model of Coregionalization under second-order space-time stationarity. Simple and ordinary space-time kriging systems are compared to simple and ordinary cokriging and their differences for unbiasedness conditions are underlined. The ordinary space-time kriging estimation then is applied to simulated data. Prediction variances and prediction errors are compared with those for ordinary kriging and cokriging under different unbiasedness conditions using a cross validation. The results show that spa...
Abstract — Kriging is a spatial prediction method, which can predict at any location and return a me...
In monitoring the environment one often wishes to detect the temporal trend in a variable that varie...
Many branches within geography deal with variables that vary not only in space but also in time. The...
This report deals with Kriging, a spatial interpolation-method that enables making predictions of th...
Kriging techniques are regression methods used for evaluation of continuous spatial processes. If th...
Space-time correlation modeling is one of the crucial steps of traditional structural analysis, sinc...
Simple cokriging of components of a p-dimensional second-order stationary random process is consider...
In this survey we present various classical geostatistical prediction methods with a focus on interp...
Geostatistics is a popular class of statistical methods for estimating, or predicting, the value of ...
Kriging based on Gaussian random fields is widely used in reconstructing unknown functions. The krig...
We present and compare functional and spatio-temporal (Sp.T.) kriging approaches to predict spatial ...
We present and compare functional and spatio-temporal (Sp.T.) kriging approaches to predict spatial ...
One of the approaches for forecasting future values of a time series or unknown spatial data is krig...
Continuous-time Gaussian processes make it possible to model irregularly sampled time series. The pr...
In this article we have used wide applicable classes of spatio‐temporal nonseparable and separable c...
Abstract — Kriging is a spatial prediction method, which can predict at any location and return a me...
In monitoring the environment one often wishes to detect the temporal trend in a variable that varie...
Many branches within geography deal with variables that vary not only in space but also in time. The...
This report deals with Kriging, a spatial interpolation-method that enables making predictions of th...
Kriging techniques are regression methods used for evaluation of continuous spatial processes. If th...
Space-time correlation modeling is one of the crucial steps of traditional structural analysis, sinc...
Simple cokriging of components of a p-dimensional second-order stationary random process is consider...
In this survey we present various classical geostatistical prediction methods with a focus on interp...
Geostatistics is a popular class of statistical methods for estimating, or predicting, the value of ...
Kriging based on Gaussian random fields is widely used in reconstructing unknown functions. The krig...
We present and compare functional and spatio-temporal (Sp.T.) kriging approaches to predict spatial ...
We present and compare functional and spatio-temporal (Sp.T.) kriging approaches to predict spatial ...
One of the approaches for forecasting future values of a time series or unknown spatial data is krig...
Continuous-time Gaussian processes make it possible to model irregularly sampled time series. The pr...
In this article we have used wide applicable classes of spatio‐temporal nonseparable and separable c...
Abstract — Kriging is a spatial prediction method, which can predict at any location and return a me...
In monitoring the environment one often wishes to detect the temporal trend in a variable that varie...
Many branches within geography deal with variables that vary not only in space but also in time. The...