عنوان

Advanced spatial modeling with stochastic partial differential equations using R and INLA /

(Number (ISBN

0429031890

(Number (ISBN

0429626576

(Number (ISBN

0429628218

(Number (ISBN

0429629850

(Number (ISBN

9780429031892

(Number (ISBN

9780429626579

(Number (ISBN

9780429628214

(Number (ISBN

9780429629853

Erroneous ISBN

1138369853

Erroneous ISBN

9781138369856

Title Proper

Advanced spatial modeling with stochastic partial differential equations using R and INLA /

General Material Designation

[Book]

First Statement of Responsibility

Elias Krainski [and seven others].

Place of Publication, Distribution, etc.

Boca Raton, FL :

Name of Publisher, Distributor, etc.

CRC Press, Taylor & Francis Group,

Date of Publication, Distribution, etc.

[2019]

Specific Material Designation and Extent of Item

1 online resource (xiii, 283 pages)

Text of Note

Includes bibliographical references and index.

Text of Note

Modeling spatial and spatio-temporal continuous processes is an important and challenging problem in spatial statistics. Advanced Spatial Modeling with Stochastic Partial Differential Equations Using R and INLA describes in detail the stochastic partial differential equations (SPDE) approach for modeling continuous spatial processes with a Matrn covariance, which has been implemented using the integrated nested Laplace approximation (INLA) in the R-INLA package. Key concepts about modeling spatial processes and the SPDE approach are explained with examples using simulated data and real applications. This book has been authored by leading experts in spatial statistics, including the main developers of the INLA and SPDE methodologies and the R-INLA package. It also includes a wide range of applications: * Spatial and spatio-temporal models for continuous outcomes * Analysis of spatial and spatio-temporal point patterns * Coregionalization spatial and spatio-temporal models * Measurement error spatial models * Modeling preferential sampling * Spatial and spatio-temporal models with physical barriers * Survival analysis with spatial effects * Dynamic space-time regression * Spatial and spatio-temporal models for extremes * Hurdle models with spatial effects * Penalized Complexity priors for spatial models All the examples in the book are fully reproducible. Further information about this book, as well as the R code and datasets used, is available from the book website at http://www.r-inla.org/spde-book. The tools described in this book will be useful to researchers in many fields such as biostatistics, spatial statistics, environmental sciences, epidemiology, ecology and others. Graduate and Ph.D. students will also find this book and associated files a valuable resource to learn INLA and the SPDE approach for spatial modeling.

Source for Acquisition/Subscription Address

Taylor & Francis

Stock Number

9780429031892

Title

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

International Standard Book Number

9781138369856

Laplace transformation.

Mathematical models.

R (Computer program language)

Stochastic differential equations.

Stochastic processes.

Laplace transformation.

Mathematical models.

MATHEMATICS / Applied

MATHEMATICS / Probability & Statistics / General

R (Computer program language)

Stochastic differential equations.

Stochastic processes.

MAT-- 003000

MAT-- 029000

PBT

Number

Edition

Class number

Book number

Krainski, E. T., (Elias T.)

Date of Transaction

20200822162305.0

Cataloguing Rules (Descriptive Conventions))

pn

Electronic name

[Book]

Y