Statistics for spatio-temporal data
A state-of-the-art presentation of spatio-temporal processes, bridging classic ideas with modern hierarchical statistical modeling concepts and the latest computational methods From understanding environmental processes and climate trends to developing new technologies for mapping public-health data and the spread of invasive-species, there is a high demand for statistical analyses of data that take spatial, temporal, and spatio-temporal information into account. Statistics for Spatio-Temporal …
Read More ↓Title Statements
- Full title :Statistics for spatio-temporal data / Noel Cressie, Christopher K. Wikle.
Summary
A state-of-the-art presentation of spatio-temporal processes, bridging classic ideas with modern hierarchical statistical modeling concepts and the latest computational methods From understanding environmental processes and climate trends to developing new technologies for mapping public-health data and the spread of invasive-species, there is a high demand for statistical analyses of data that take spatial, temporal, and spatio-temporal information into account. Statistics for Spatio-Temporal Data presents a systematic approach to key quantitative techniques that incorporate the latest advances in statistical computing as well as hierarchical, particularly Bayesian, statistical modeling, with an emphasis on dynamical spatio-temporal models. Cressie and Wikle supply a unique presentation that incorporates ideas from the areas of time series and spatial statistics as well as stochastic processes. Beginning with separate treatments of temporal data and spatial data, the book combines these concepts to discuss spatio-temporal statistical methods for understanding complex processes. Topics of coverage include:* Exploratory methods for spatio-temporal data, including visualization, spectral analysis, empirical orthogonal function analysis, and LISAs* Spatio-temporal covariance functions, spatio-temporal kriging, and time series of spatial processes* Development of hierarchical dynamical spatio-temporal models (DSTMs), with discussion of linear and nonlinear DSTMs and computational algorithms for their implementation* Quantifying and exploring spatio-temporal variability in scientific applications, including case studies based on real-world environmental data Throughout the book, interesting applications demonstrate the relevance of the presented concepts.
Read More ↓Edition Statements
- Publication Date:2011.
Publication Statements
- Publisher(s):Wiley
- Place of Publication:Hoboken, N.J
- Language:eng
- Publication Date:2011.
The Physical Object
- Description:XXII, 588 Seiten : : Illustrationen, Diagramme, Karten.
Edition Identifiers
- ISBN:9780471692744, 0471692743
- oclc:ocn699885415
Subjects
Writers
More from this Series
No reviews yet. Be the first to rate this work.
Related Works
more →
Wahrscheinlichkeitstheorie
Ranked set sampling
Generalized Linear Models
Methodological developments in data linkage
Compositional Data Analysis: Theory and Applications
The elements of statistical learning: data mining, inference, and prediction
Hastie, Trevor
Statistics and experimental design for toxicologists and pharmacologists
Gad, Shayne C.
Applied longitudinal data analysis: modeling change and event occurrence
Singer, Judith D.
Files & Downloads
-
Statistics for Spatio-Temporal Data -- (.epub)
EPUB · 7.8 MB · updated -
Statistics for Spatio-Temporal Data -- (.mobi)
MOBI · 9.9 MB · updated
Rate & Review