This book is characterized by extremely rich content and presents in a clear and simple way both classical contributions of random field theory and statistical analysis, together with specialized material in spatial data modeling. Theory and practice, with examples, are balanced in a unique way. The book includes excellent and timely advice, clarifications and discussions on computational aspects which may be useful in dealing with real problems of spatial data analysis. With a total of 867 pages comprising 17 chapters, it offers in-depth coverage of a vast array of topics which focus on spatial random fields, their characteristics, theoretical and practical issues of spatial modeling (parameter estimation, prediction, simulation) and their potential application in different scientific and engineering disciplines, where large spatial data are often available.
Dionissios T. Hristopulos: Random Fields for Spatial Data Modeling. A Primer for Scientists and Engineers
De Iaco, S.
2021-01-01
Abstract
This book is characterized by extremely rich content and presents in a clear and simple way both classical contributions of random field theory and statistical analysis, together with specialized material in spatial data modeling. Theory and practice, with examples, are balanced in a unique way. The book includes excellent and timely advice, clarifications and discussions on computational aspects which may be useful in dealing with real problems of spatial data analysis. With a total of 867 pages comprising 17 chapters, it offers in-depth coverage of a vast array of topics which focus on spatial random fields, their characteristics, theoretical and practical issues of spatial modeling (parameter estimation, prediction, simulation) and their potential application in different scientific and engineering disciplines, where large spatial data are often available.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.