The anisotropy in particular environmental phenomena is detected when behavior of a physical process differs in different directions. In this paper geometric and zonal anisotropies are considered. Various methods of geostatistical analysis, also isotropic and geometrical anisotropic variogram models are compared and applied for the Curonian lagoon depth data. The results demonstrate that after robust estimation, i.e. elimination of outliers and after elimination of geometric anisotropy the precision of prediction and adequacy of models are much better. All computations have been performed by means of gstat, base and spatial packages of R system. Prediction results are compared with the results of research where outliers and geometric anisot...
The study on spatial variability of soil properties performed through geostatistical techniques all...
Matheron's usual variogram estimator can result in unreliable variograms when data are strongly asym...
The typical goal of geostatistical analysis is to interpolate values of variable under consideration...
The article deals with the analysis of anisotropic variogram models for prediction of the Curonian l...
The variogram is a basic tool in geostatistics. It expresses the variability between pairs of observ...
Statistical stationarity is a key assumption for the many modeling techniques based on variograms an...
Many heterogeneous media and environmental processes are statistically anisotropic, that is, their m...
This work addresses the question of building useful and valid models of anisotropic variograms for s...
Summarization: Many heterogeneous media and environmental processes are statistically anisotropic, t...
For modeling spatial processes, we propose rich classes of range anisotropic covariance structures t...
The variogram is a basic tool in geostatistics. In the case of an assumed isotropic process, it is u...
The Matérn correlation function provides great flexibility for modeling spatially correlated random ...
The Matérn correlation function provides great flexibility for modeling spatially correlated random...
This thesis concerns the development, estimation and investigation of a general anisotropic spatial ...
The efficient mapping of environmental hazards requires the development of methods for the analysis ...
The study on spatial variability of soil properties performed through geostatistical techniques all...
Matheron's usual variogram estimator can result in unreliable variograms when data are strongly asym...
The typical goal of geostatistical analysis is to interpolate values of variable under consideration...
The article deals with the analysis of anisotropic variogram models for prediction of the Curonian l...
The variogram is a basic tool in geostatistics. It expresses the variability between pairs of observ...
Statistical stationarity is a key assumption for the many modeling techniques based on variograms an...
Many heterogeneous media and environmental processes are statistically anisotropic, that is, their m...
This work addresses the question of building useful and valid models of anisotropic variograms for s...
Summarization: Many heterogeneous media and environmental processes are statistically anisotropic, t...
For modeling spatial processes, we propose rich classes of range anisotropic covariance structures t...
The variogram is a basic tool in geostatistics. In the case of an assumed isotropic process, it is u...
The Matérn correlation function provides great flexibility for modeling spatially correlated random ...
The Matérn correlation function provides great flexibility for modeling spatially correlated random...
This thesis concerns the development, estimation and investigation of a general anisotropic spatial ...
The efficient mapping of environmental hazards requires the development of methods for the analysis ...
The study on spatial variability of soil properties performed through geostatistical techniques all...
Matheron's usual variogram estimator can result in unreliable variograms when data are strongly asym...
The typical goal of geostatistical analysis is to interpolate values of variable under consideration...