Indicator and multivariate geostatistics for spatial prediction
نویسندگان
چکیده
منابع مشابه
Cross-Covariance Functions for Multivariate Geostatistics
Continuously indexed datasets with multiple variables have become ubiquitous in the geophysical, ecological, environmental and climate sciences, and pose substantial analysis challenges to scientists and statisticians. For many years, scientists developed models that aimed at capturing the spatial behavior for an individual process; only within the last few decades has it become commonplace to ...
متن کاملRobust Multivariate Methods in Geostatistics
Two robust approaches to principal component analysis and factor analysis are presented. The different methods are compared, and properties are discussed. As an application we use a large geochemical data set which was analyzed in detail by univariate (geo-)statistical methods. We explain the advantages of applying robust multivariate methods.
متن کاملGeostatistics and spatial analysis in biological anthropology.
A variety of methods have been used to make evolutionary inferences based on the spatial distribution of biological data, including reconstructing population history and detection of the geographic pattern of natural selection. This article provides an examination of geostatistical analysis, a method used widely in geology but which has not often been applied in biological anthropology. Geostat...
متن کاملMultivariate Feature Extraction for Prediction of Future Gene Expression Profile
Introduction: The features of a cell can be extracted from its gene expression profile. If the gene expression profiles of future descendant cells are predicted, the features of the future cells are also predicted. The objective of this study was to design an artificial neural network to predict gene expression profiles of descendant cells that will be generated by division/differentiation of h...
متن کاملMultivariate spatial-temporal modeling and prediction of speciated fine particles.
Fine particulate matter (PM(2.5)) is an atmospheric pollutant that has been linked to serious health problems, including mortality. PM(2.5) is a mixture of pollutants, and it has five main components: sulfate, nitrate, total carbonaceous mass, ammonium, and crustal material. These components have complex spatial-temporal dependency and cross dependency structures. It is important to gain insigh...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Geo-spatial Information Science
سال: 2008
ISSN: 1009-5020,1993-5153
DOI: 10.1007/s11806-008-0129-1