Spatiotemporal processes occur in many areas of earth sciences and engineering. However, most of the available theoretical tools and techniques of space-time daft processing have been designed to operate exclusively in time or in space, and the importance of spatiotemporal variability was not fully appreciated until recently. To address this problem, a systematic framework of spatiotemporal random field (S/TRF) models for geoscience/engineering applications is presented and developed in this thesis.The space-tune continuity characterization is one of the most important aspects in S/TRF modelling, where the space-time continuity is displayed with experimental spatiotemporal variograms, summarized in terms of space-time continuity hypotheses,...
Natural processes encountered in mining, hydrogeologic, environmental, etc. applications usually are...
In this paper, a framework for stochastic spatiotemporal modeling of daily precipitation in a hindca...
This paper analyzes the use of stratification in the modeling of dependence for regionalized variabl...
Doctor of PhilosophyDepartment of StatisticsJuan DuIt is common to assume the spatial or spatio-temp...
Many branches within geography deal with variables that vary not only in space but also in time. The...
Summarization: We conduct a spatiotemporal geostatistical analysis of groundwater level data using s...
Statistical Methods for Spatio-Temporal Systems presents current statistical research issues on spat...
A generator of spatio-temporal pseudo-random Gaussian fields that satisfy the “proportionality of sc...
In the following, we discuss a procedure for interpolating a spatial-temporal stochastic process. We...
Heterogeneity-preserving property models of subsurface regions are commonly constructed by means of ...
Modeling of spatio-temporal processes is critical in many fields such as environmental sciences, met...
We present a novel approach named Physics-based Residual Kriging for the statistical prediction of s...
Doctor of PhilosophyDepartment of StatisticsJuan DuIn view of multivariate nature of general spatio-...
Modelisation and prediction of environmental phenomena, which typically show dependence in space and...
Prepared under support of the Dept. of Energy through M.I.T. Energy Laboratory and the Office of Sur...
Natural processes encountered in mining, hydrogeologic, environmental, etc. applications usually are...
In this paper, a framework for stochastic spatiotemporal modeling of daily precipitation in a hindca...
This paper analyzes the use of stratification in the modeling of dependence for regionalized variabl...
Doctor of PhilosophyDepartment of StatisticsJuan DuIt is common to assume the spatial or spatio-temp...
Many branches within geography deal with variables that vary not only in space but also in time. The...
Summarization: We conduct a spatiotemporal geostatistical analysis of groundwater level data using s...
Statistical Methods for Spatio-Temporal Systems presents current statistical research issues on spat...
A generator of spatio-temporal pseudo-random Gaussian fields that satisfy the “proportionality of sc...
In the following, we discuss a procedure for interpolating a spatial-temporal stochastic process. We...
Heterogeneity-preserving property models of subsurface regions are commonly constructed by means of ...
Modeling of spatio-temporal processes is critical in many fields such as environmental sciences, met...
We present a novel approach named Physics-based Residual Kriging for the statistical prediction of s...
Doctor of PhilosophyDepartment of StatisticsJuan DuIn view of multivariate nature of general spatio-...
Modelisation and prediction of environmental phenomena, which typically show dependence in space and...
Prepared under support of the Dept. of Energy through M.I.T. Energy Laboratory and the Office of Sur...
Natural processes encountered in mining, hydrogeologic, environmental, etc. applications usually are...
In this paper, a framework for stochastic spatiotemporal modeling of daily precipitation in a hindca...
This paper analyzes the use of stratification in the modeling of dependence for regionalized variabl...