Advanced spatial modeling with stochastic partial differential equations using R and INLA. (2018)

• Record Type: Book
• Further Information: Note: E.T. Krainski [and seven others].
• Authors: Krainski, E. T (Elias T.); Gómez-Rubio, Virgilio; Bakka, Haakon; Lenzi, Amanda; Castro-Camilo, Daniela; Simpson, Daniel; Lindgren, Finn; Rue, Håvard
• Contents: Preamble What this book is and isn’t The Integrated Nested Laplace Approximation and the R-INLA package Introduction The INLA method A simple example Additional arguments and control options Manipulating the posterior marginals Advanced features Introduction to spatial modeling Introduction The SPDE approach A toy example Projection of the random field Prediction Triangulation details and examples Tools for mesh assessment Non-Gaussian response: Precipitation in Paraná More than one likelihood Coregionalization model Joint modeling: Measurement error model Copying part of or the entire linear predictor Point processes and preferential sampling Introduction Including a covariate in the log-Gaussian Cox process Geostatistical inference under preferential sampling Spatial non-stationarity Explanatory variables in the covariance The Barrier model Barrier model for noise data in Albacete (Spain) Risk assessment using non-standard likelihoods Survival analysis Models for extremes Space-time models Discrete time domain Continuous time domain Lowering the resolution of a spatio-temporal model Conditional simulation: Combining two meshes Space-time applications Space-time coregionalization model Dynamic regression example Space-time point process: Burkitt example Large point process dataset Accumulated rainfall: Hurdle Gamma model List of symbols and notation Packages used in the book
• Edition: 1st
• Publisher Details: Boca Raton : Chapman & Hall/CRC
• Publication Date: 2018
• Extent: 1 online resource
• Subjects: 519.22; Stochastic differential equations; Mathematical models; Stochastic processes; Laplace transformation; R (Computer program language)
• Languages: English
• ISBNs: 9780429628214; 9780429629853; 9780429626579; 9780429031892
• Related ISBNs: 9781138369856
• Notes: Note: Description based on CIP data; resource not viewed.
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