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eBook Model-based Geostatistics (Springer Series in Statistics) ePub

eBook Model-based Geostatistics (Springer Series in Statistics) ePub

by Peter J. Diggle,Paulo Justiniano Ribeiro

  • ISBN: 0387329072
  • Category: Mathematics
  • Subcategory: Math Science
  • Author: Peter J. Diggle,Paulo Justiniano Ribeiro
  • Language: English
  • Publisher: Springer (March 12, 2007)
  • Pages: 228
  • ePub book: 1179 kb
  • Fb2 book: 1718 kb
  • Other: docx lrf doc lrf
  • Rating: 4.1
  • Votes: 733

Description

Model-based Geostatistics. Authors: Diggle, Peter, Ribeiro, Paulo Justiniano. It is clearly intended for graduate students in statistics and to a lesser extent those simply using geostatistics

Model-based Geostatistics. It is clearly intended for graduate students in statistics and to a lesser extent those simply using geostatistics. Each chapter has exercises which are a mix of applied and theoretical, the applied exercises often using one of the associated R packages. €¦ This volume is an important contribution to the literature ….

Peter J. Diggle Paulo J. Ribeiro Jr. Model-based Geostatistics. This book takes the same point of view. Geostatistics refers to the sub-branch of spatial statistics in which the data consist of a finite sample of measured values relating to an underlying spatially continuous phenomenon. Examples include: heights above sea-level in a topographical survey; pollution measurements from a finite network of monitoring stations; determinations of soil properties from core samples; insect counts from traps at selected locations. We aim to produce an applied statistical counterpart to Stein (1999), who gives a rigorous mathematical theory of kriging.

I was very interested in "Model-based Geostatistics" by Diggle and Ribeiro because I teach a course in. .I was unaware that the Matheron work was "developed largely independently of the mainstream of spatial geostatistics.

I was very interested in "Model-based Geostatistics" by Diggle and Ribeiro because I teach a course in applied geostatistics. The book was informative. The preface was interesting read because most of the geostatistics of which I am familiar is based upon the work of Matheron. Topics that were of interest to me were ones such as . Exploratory data analysis.

Model-Based Geostatistics is appropriate as a textbook for applied geostatistics or as supportive material for spatial statistics for graduate students. Series: Springer Series in Statistics. €¦ Overall, this book provides a comprehensive summary of model-based geostatitics. It is easy to follow even without a very strong statistical background. €¦ In addition, the book offered at a reasonable price.

Geostatistics is concerned with estimation and prediction problems for . The authors have used the material in MSc-level statistics courses.

Geostatistics is concerned with estimation and prediction problems for spatially continuous phenomena, using data obtained at a limited number of spatial locations. The name reflects its origins in mineral exploration, but the methods are now used in a wide range of settings including public health and the physical and environmental sciences. Model-based geostatistics refers to the application of general statistical principles of modeling and inference to geostatistical problems. This volume is the first book-length treatment of model-based geostatistics.

Springer Series in Statistics. Geostatistics is concerned with. Model-based geostatistics refe Geostatistics is concerned with estimation and prediction problems for spatially continuous phenomena, using data obtained at a limited number of spatial locations.

by Peter J. Diggle & Paulo Justiniano Ribeiro &. and statistics quickly. It brings together many of the main ideas in modern statistics in one place. Large Sample Techniques for Statistics (Springer Texts in Statistics). 37 MB·3,951 Downloads. Large-sample techniques provide solutions to many practical problems; they.

Автор: Diggle Название: Model-based Geostatistics ISBN: 0387329072 .

Model-based geostatistics refers to the application of general statistical principles of modeling and inference to geostatistical problems. Geospatial statistics analysis using stepwise regression, ordinary least squares (OLS), variogram, kriging, spatial auto-regression, binary classification trees, cokriging, and geospatial models for presence and absence data.

Электронная книга "Model-based Geostatistics", Peter Diggle, Paulo Justiniano Ribeiro. Эту книгу можно прочитать в Google Play Книгах на компьютере, а также на устройствах Android и iOS. Выделяйте текст, добавляйте закладки и делайте заметки, скачав книгу "Model-based Geostatistics" для чтения в офлайн-режиме.

This volume is the first book-length treatment of model-based geostatistics. The text is expository, emphasizing statistical methods and applications rather than the underlying mathematical theory. Analyses of datasets from a range of scientific contexts feature prominently, and simulations are used to illustrate theoretical results. Readers can reproduce most of the computational results in the book by using the authors' software package, geoR, whose usage is illustrated in a computation section at the end of each chapter. The book assumes a working knowledge of classical and Bayesian methods of inference, linear models, and generalized linear models.

Comments

Unh Unh
There's no better way to learn something, but practicing. This concise and direct book shows you what you must know, who you may apply it and the most important of all, how you can do it using R statistical software (an amazing tool by the way). Geostatistics may be tricky sometimes, and as all the statistics you must be sure you are doing the right thing the right way. This book you help you in this task just the way you need.
Elastic Skunk Elastic Skunk
I was very interested in "Model-based Geostatistics" by Diggle and Ribeiro because I teach a course in applied geostatistics. The book was informative. The preface was interesting read because most of the geostatistics of which I am familiar is based upon the work of Matheron. I was unaware that the Matheron work was "developed largely independently of the mainstream of spatial geostatistics." Topics that were of interest to me were ones such as 2.3 Exploratory data analysis. This concept is often not emphasized enough. Another interesting section was 6.4 What does Kriging actually do to the data? Section 8.1 Choosing the study region was interesting, but, as the authors state "...is often pre-determined by the context of the investigation...." Choosing the sample locations: Uniform designs (8.2) was another interesting section.
Coiriel Coiriel
excellent!
Kieel Kieel
The book was shipped as soon as possible. Everything was perfect!