Title spatial and spatio-temporal geostatistical modelling, prediction and simulation Description variogram modelling; simple, ordinary and universal point or block (co)kriging, sequen-tial Gaussian or indicator (co)simulation; variogram and variogram map plotting utility functions. Depends R (> = 2.10) Imports methods, lattice, sp (> = 0.9-72), zoo, spacetime (> = 1.0-0),FN
Spatial statistics are useful in subjects as diverse as climatology, ecology, economics, environment...
The spatial prediction/simulation of point values from areal data of the same attribute is ad-dresse...
Spatial and spatio-temporal data are not new. They have always been here. However, until fairly rece...
Geostatistics is a popular class of statistical methods for estimating, or predicting, the value of ...
Abstract Chapter3: Exploratory data analysis and prediction in time series modeling are not typicall...
Many branches within geography deal with variables that vary not only in space but also in time. The...
Space-time correlation modeling is one of the crucial steps of traditional structural analysis, sinc...
Description SciKit-Gstat is a scipy-styled geostatistical toolbox for variogram estimation. It incl...
SciKit-Gstat is a scipy-styled analysis module for geostatistics. It includes two base classes Vario...
The variogram model is one of the most relevant parameters in geostatistical estimation and simulat...
Geostatistical spatio-temporal models provide a probabilistic framework for data analysis and predic...
Geostatistics is a scientific field which provides methods for processing spatial data. In our proj...
This paper gives an overview of some of the possible applications of the variogram cloud in geostati...
SciKit-Gstat is a scipy-styled analysis module for geostatistics. It includes two base classes Vario...
Geostatistics: Modeling Spatial Uncertainty by J.-P. Chilès and P. Delfiner publishedin 1999 has bee...
Spatial statistics are useful in subjects as diverse as climatology, ecology, economics, environment...
The spatial prediction/simulation of point values from areal data of the same attribute is ad-dresse...
Spatial and spatio-temporal data are not new. They have always been here. However, until fairly rece...
Geostatistics is a popular class of statistical methods for estimating, or predicting, the value of ...
Abstract Chapter3: Exploratory data analysis and prediction in time series modeling are not typicall...
Many branches within geography deal with variables that vary not only in space but also in time. The...
Space-time correlation modeling is one of the crucial steps of traditional structural analysis, sinc...
Description SciKit-Gstat is a scipy-styled geostatistical toolbox for variogram estimation. It incl...
SciKit-Gstat is a scipy-styled analysis module for geostatistics. It includes two base classes Vario...
The variogram model is one of the most relevant parameters in geostatistical estimation and simulat...
Geostatistical spatio-temporal models provide a probabilistic framework for data analysis and predic...
Geostatistics is a scientific field which provides methods for processing spatial data. In our proj...
This paper gives an overview of some of the possible applications of the variogram cloud in geostati...
SciKit-Gstat is a scipy-styled analysis module for geostatistics. It includes two base classes Vario...
Geostatistics: Modeling Spatial Uncertainty by J.-P. Chilès and P. Delfiner publishedin 1999 has bee...
Spatial statistics are useful in subjects as diverse as climatology, ecology, economics, environment...
The spatial prediction/simulation of point values from areal data of the same attribute is ad-dresse...
Spatial and spatio-temporal data are not new. They have always been here. However, until fairly rece...
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