Add to ORKGIn this paper we briefly illustrate some exploratory techniques born in the geostatistical framework. Applications to rainfall data are reported to illustrate the proposed approaches
This contributed volume features invited papers on current models and statistical methods for spatia...
There are numerous methods for data filling in hydrology. Most, however, are based on correlations w...
Non-separable models are receiving a lot of attention, since they are more flexible to handle empiri...
A large number of hydrological phenomena may be regarded as realizations of space-time random functi...
This paper introduces the geostatistical method. Originally devised to treat problems that arise whe...
Modeling and prediction multivariate geostatistical techniques can be successfully applied to study ...
Modeling and prediction multivariate geostatistical techniques can be successfully applied to study ...
The third edition of this very successful text book provides an introduction to geostatistics stress...
Many branches within geography deal with variables that vary not only in space but also in time. The...
Many branches within geography deal with variables that vary not only in space but also in time. The...
Rainfall can be modeled as a spatially correlated random field superimposed on a background mean val...
Rainfall can be modeled as a spatially correlated random field superimposed on a background mean val...
In various environmental studies multivariate spatial–temporal correlated data are involved, hence ...
An environmental data set often concerns different correlated variables measured at some locations o...
This contributed volume features invited papers on current models and statistical methods for spatia...
This contributed volume features invited papers on current models and statistical methods for spatia...
There are numerous methods for data filling in hydrology. Most, however, are based on correlations w...
Non-separable models are receiving a lot of attention, since they are more flexible to handle empiri...
A large number of hydrological phenomena may be regarded as realizations of space-time random functi...
This paper introduces the geostatistical method. Originally devised to treat problems that arise whe...
Modeling and prediction multivariate geostatistical techniques can be successfully applied to study ...
Modeling and prediction multivariate geostatistical techniques can be successfully applied to study ...
The third edition of this very successful text book provides an introduction to geostatistics stress...
Many branches within geography deal with variables that vary not only in space but also in time. The...
Many branches within geography deal with variables that vary not only in space but also in time. The...
Rainfall can be modeled as a spatially correlated random field superimposed on a background mean val...
Rainfall can be modeled as a spatially correlated random field superimposed on a background mean val...
In various environmental studies multivariate spatial–temporal correlated data are involved, hence ...
An environmental data set often concerns different correlated variables measured at some locations o...
This contributed volume features invited papers on current models and statistical methods for spatia...
This contributed volume features invited papers on current models and statistical methods for spatia...
There are numerous methods for data filling in hydrology. Most, however, are based on correlations w...
Non-separable models are receiving a lot of attention, since they are more flexible to handle empiri...