Author: Steve McKillup Publisher: Cambridge University Press ISBN: 0521763223 Category : Mathematics Languages : en Pages : 413
Book Description
This reader-friendly introduction to geostatistics demystifies complex concepts and makes formulas and statistical tests easy to apply. With wide-ranging examples from topics across the Earth and environmental sciences, and worked examples at the end of each chapter, this book can be used for undergraduate courses or for self-study and reference.
Author: Steve McKillup Publisher: Cambridge University Press ISBN: 1139502948 Category : Medical Languages : en Pages : 430
Book Description
An understanding of statistics and experimental design is essential for life science studies, but many students lack a mathematical background and some even dread taking an introductory statistics course. Using a refreshingly clear and encouraging reader-friendly approach, this book helps students understand how to choose, carry out, interpret and report the results of complex statistical analyses, critically evaluate the design of experiments and proceed to more advanced material. Taking a straightforward conceptual approach, it is specifically designed to foster understanding, demystify difficult concepts and encourage the unsure. Even complex topics are explained clearly, using a pictorial approach with a minimum of formulae and terminology. Examples of tests included throughout are kept simple by using small data sets. In addition, end-of-chapter exercises, new to this edition, allow self-testing. Handy diagnostic tables help students choose the right test for their work and remain a useful refresher tool for postgraduates.
Author: Hans Wackernagel Publisher: Springer Science & Business Media ISBN: 3662035502 Category : Science Languages : en Pages : 259
Book Description
An introduction to geostatistics stressing the multivariate aspects for scientists, engineers and statisticians. The book presents a brief review of statistical concepts, a detailed introduction to linear geostatistics, and an account of three basic methods of multivariate analysis. Applications from very different areas of science, as well as exercises with solutions, are provided to help convey the general ideas. In this second edition, the chapters regarding normal kriging and cokriging have been restructured and the section on non-stationary geostatistics has been entirely rewritten.
Author: Richard Webster Publisher: John Wiley & Sons ISBN: 9780470517260 Category : Mathematics Languages : en Pages : 330
Book Description
Geostatistics is essential for environmental scientists. Weather and climate vary from place to place, soil varies at every scale at which it is examined, and even man-made attributes – such as the distribution of pollution – vary. The techniques used in geostatistics are ideally suited to the needs of environmental scientists, who use them to make the best of sparse data for prediction, and top plan future surveys when resources are limited. Geostatistical technology has advanced much in the last few years and many of these developments are being incorporated into the practitioner’s repertoire. This second edition describes these techniques for environmental scientists. Topics such as stochastic simulation, sampling, data screening, spatial covariances, the variogram and its modeling, and spatial prediction by kriging are described in rich detail. At each stage the underlying theory is fully explained, and the rationale behind the choices given, allowing the reader to appreciate the assumptions and constraints involved.
Author: Yongwan Chun Publisher: SAGE ISBN: 1446272117 Category : Reference Languages : en Pages : 201
Book Description
"Ideal for anyone who wishes to gain a practical understanding of spatial statistics and geostatistics. Difficult concepts are well explained and supported by excellent examples in R code, allowing readers to see how each of the methods is implemented in practice" - Professor Tao Cheng, University College London Focusing specifically on spatial statistics and including components for ArcGIS, R, SAS and WinBUGS, this book illustrates the use of basic spatial statistics and geostatistics, as well as the spatial filtering techniques used in all relevant programs and software. It explains and demonstrates techniques in: spatial sampling spatial autocorrelation local statistics spatial interpolation in two-dimensions advanced topics including Bayesian methods, Monte Carlo simulation, error and uncertainty. It is a systematic overview of the fundamental spatial statistical methods used by applied researchers in geography, environmental science, health and epidemiology, population and demography, and planning. A companion website includes digital R code for implementing the analyses in specific chapters and relevant data sets to run the R codes.
Author: Imran Ahmad Dar Publisher: BoD – Books on Demand ISBN: 9533078618 Category : Science Languages : en Pages : 664
Book Description
The studies of Earth's history and of the physical and chemical properties of the substances that make up our planet, are of great significance to our understanding both of its past and its future. The geological and other environmental processes on Earth and the composition of the planet are of vital importance in locating and harnessing its resources. This book is primarily written for research scholars, geologists, civil engineers, mining engineers, and environmentalists. Hopefully the text will be used by students, and it will continue to be of value to them throughout their subsequent professional and research careers. This does not mean to infer that the book was written solely or mainly with the student in mind. Indeed from the point of view of the researcher in Earth and Environmental Science it could be argued that this text contains more detail than he will require in his initial studies or research.
Author: Jean-Paul Chilès Publisher: John Wiley & Sons ISBN: 0470317833 Category : Mathematics Languages : en Pages : 718
Book Description
A novel, practical approach to modeling spatial uncertainty. This book deals with statistical models used to describe natural variables distributed in space or in time and space. It takes a practical, unified approach to geostatistics-integrating statistical data with physical equations and geological concepts while stressing the importance of an objective description based on empirical evidence. This unique approach facilitates realistic modeling that accounts for the complexity of natural phenomena and helps solve economic and development problems-in mining, oil exploration, environmental engineering, and other real-world situations involving spatial uncertainty. Up-to-date, comprehensive, and well-written, Geostatistics: Modeling Spatial Uncertainty explains both theory and applications, covers many useful topics, and offers a wealth of new insights for nonstatisticians and seasoned professionals alike. This volume: * Reviews the most up-to-date geostatistical methods and the types of problems they address. * Emphasizes the statistical methodologies employed in spatial estimation. * Presents simulation techniques and digital models of uncertainty. * Features more than 150 figures and many concrete examples throughout the text. * Includes extensive footnoting as well as a thorough bibliography. Geostatistics: Modeling Spatial Uncertainty is the only geostatistical book to address a broad audience in both industry and academia. An invaluable resource for geostatisticians, physicists, mining engineers, and earth science professionals such as petroleum geologists, geophysicists, and hydrogeologists, it is also an excellent supplementary text for graduate-level courses in related subjects.
Author: P. K. Kitanidis Publisher: Cambridge University Press ISBN: 9780521587471 Category : Science Languages : en Pages : 276
Book Description
Engineers and applied geophysicists routinely encounter interpolation and estimation problems when analysing data from field observations. Introduction to Geostatistics presents practical techniques for the estimation of spatial functions from sparse data. The author's unique approach is a synthesis of classic and geostatistical methods with a focus on the most practical linear minimum-variance estimation methods, and includes suggestions on how to test and extend the applicability of such methods. The author includes many useful methods (often not covered in other geostatistics books) such as estimating variogram parameters, evaluating the need for a variable mean, parameter estimation and model testing in complex cases (e.g. anisotropy, variable mean, and multiple variables), and using information from deterministic mathematical models. Well illustrated with exercises and worked examples taken from hydrogeology, Introduction to Geostatistics assumes no background in statistics and is suitable for graduate-level courses in earth sciences, hydrology, and environmental engineering, and also for self-study.
Author: Hans Wackernagel Publisher: Springer Science & Business Media ISBN: 3662030985 Category : Science Languages : en Pages : 263
Book Description
Introducing geostatistics from a multivariate perspective is the main aim of this book. The idea took root while teaching geostatistics at the Centre de Geostatis tique (Ecole des Mines de Paris) over the past ten years in the two postgraduate programs DEA and CFSG. A first script of lecture notes in French originated from this activity. A specialized course on Multivariate and Exploratory Geostatistics held in September 1993 in Paris (organized in collaboration with the Department of Statistics of Trinity College Dublin) was the occasion to test some of the mate rial on a pluridisciplinary audience. Another important opportunity arose last year when giving a lecture on Spatial Statistics during the summer term at the Department of Statistics of the University of Washington at Seattle, where part of this manuscript was distributed in an early version. Short accounts were also given during COMETT and TEMPUS courses on geostatistics for environment al studies in Fontainebleau, Freiberg, Rome and Prague, which were sponsored by the European Community. I wish to thank the participants of these various courses for their stimulating questions and comments. Among the organizers of these courses, I particularly want to acknowledge the support received from Georges Matheron, Pierre Chau vet, Margaret Armstrong, John Haslett and Paul Sampson. Michel Grzebyk has made valuable comments on Chapters 26 and 27, which partly summarize some of his contributions to the field.
Author: S. Henley Publisher: Springer Science & Business Media ISBN: 9400981171 Category : Science Languages : en Pages : 156
Book Description
The ideas in this book have been developed over the past three or four years while I was working at the Institute of Geological Sciences and later for Golder Associates. During that time all of the geological modelling and resource estimation studies I participated in had data that were non-ideal in one respect or another (or just plain 'dirty'): the standard ways of handling the data with kriging or with simpler parametric methods gave reason able results, but always there were nagging doubts and some lack of confidence because of the corners that had to be cut in generat ing a model. The bimodal distribution that was assumed to be 'close enough' to normal; the pattern of rich and poor zones that was not quite a trend yet made the data very non-stationary; and the many plotted variograms that would not fit any standard model variogram: these all contributed to the feeling that there should be something that statistics could say about the cases where hardly any assumptions could be made about the properties ofthe parent population.
Proudly powered by WordPress |
Theme: Rits Blog by Crimson Themes.
Author: Steve McKillup
Author: Steve McKillup
Author: Hans Wackernagel
Author: Richard Webster
Author: Yongwan Chun
Author: Imran Ahmad Dar
Author: Jean-Paul Chilès
Author: P. K. Kitanidis
Author: Hans Wackernagel
Author: S. Henley