Statistical Methods For Spatio-Temporal Systems - Finkenstadt Barbel (Curatore); Held Leonhard (Curatore) | Libro Chapman And Hall/Crc 10/2006 - HOEPLI.it


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finkenstadt barbel (curatore); held leonhard (curatore) - statistical methods for spatio-temporal systems

Statistical Methods for Spatio-Temporal Systems

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Dettagli

Genere:Libro
Lingua: Inglese
Pubblicazione: 10/2006
Edizione: 1° edizione





Note Editore

Statistical Methods for Spatio-Temporal Systems presents current statistical research issues on spatio-temporal data modeling and will promote advances in research and a greater understanding between the mechanistic and the statistical modeling communities.Contributed by leading researchers in the field, each self-contained chapter starts with an introduction of the topic and progresses to recent research results. Presenting specific examples of epidemic data of bovine tuberculosis, gastroenteric disease, and the U.K. foot-and-mouth outbreak, the first chapter uses stochastic models, such as point process models, to provide the probabilistic backbone that facilitates statistical inference from data. The next chapter discusses the critical issue of modeling random growth objects in diverse biological systems, such as bacteria colonies, tumors, and plant populations. The subsequent chapter examines data transformation tools using examples from ecology and air quality data, followed by a chapter on space-time covariance functions. The contributors then describe stochastic and statistical models that are used to generate simulated rainfall sequences for hydrological use, such as flood risk assessment. The final chapter explores Gaussian Markov random field specifications and Bayesian computational inference via Gibbs sampling and Markov chain Monte Carlo, illustrating the methods with a variety of data examples, such as temperature surfaces, dioxin concentrations, ozone concentrations, and a well-established deterministic dynamical weather model.




Sommario

Preface Spatio-Temporal Point Processes: Methods and Applications Peter J. DiggleSpatio-Temporal Modeling-With a View to Biological GrowthEva B. Vedel Jensen, Kristjana Ýr Jónsdóttir, Jürgen Schmiegel, and Ole E. Barndorff-NielsenUsing Transforms to Analyze Space-Time ProcessesMontserrat Fuentes, Peter Guttorp, and Paul D. SampsonGeostatistical Space-Time Models, Stationarity, Separability, and Full Symmetry Tilmann Gneiting, Marc G. Genton, and Peter GuttorpSpace-Time Modeling of Rainfall for Continuous Simulation Richard E. Chandler, Valerie Isham, Enrica Bellone, Chi Yang, and Paul NorthropA Primer on Space-Time Modeling from a Bayesian Perspective Dave HigdonIndex




Trama

The first statistics book devoted to spatio-temporal models, Statistical Methods for Spatio-Temporal Systems presents current statistical research issues on spatio-temporal data modeling that will promote advances in research and a greater understanding between the mechanistic and the statistical modeling communities. The book describes recent advances and presents a variety of statistical methods, including likelihood-based, nonparametric smoothing, spectral, Fourier, wavelet, and Markov chain Monte Carlo. The methods are illustrated with color images as well as real-world examples, case studies, and applications from epidemiology, geology, and climatology. Key topics include point processes, dynamics, modeling, data analysis, Bayesian methods, and geostatistics.







Altre Informazioni

ISBN:

9781584885931

Condizione: Nuovo
Collana: Chapman & Hall/CRC Monographs on Statistics and Applied Probability
Dimensioni: 9.25 x 6.125 in Ø 1.25 lb
Formato: Copertina rigida
Illustration Notes:122 b/w images, 16 color images, 16 tables and 280 equations
Pagine Arabe: 286






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