1 Introduction 2 Introduction to probability sampling 3 Simple random sampling 4 Stratified simple random sampling 5 Systematic random sampling 6 Cluster random sampling 7 Two-stage cluster random sampling 8 Sampling with probabilities proportional to size 9 Balanced and well-spread sampling 10 Model-assisted estimation 11 Two-phase random sampling 12 Computing the required sample size 13 Model-based optimisation of probability sampling designs 14 Sampling for estimating parameters of (small) domains 15 Repeated sample surveys for monitoring population parameters 16 Introduction to sampling for mapping 17 Regular grid and spatial coverage sampling 18 Covariate space coverage sampling 19 Conditioned Latin hypercube sampling 20 Spatial response surface sampling 21 Introduction to kriging 22 Model-based optimisation of the grid spacing 23 Model-based optimisation of the sampling pattern 24 Sampling for estimating the semivariogram 25 Sampling for validation of maps 26 Design-based, model-based, and model-assisted approach for sampling and inference
Dick J. Brus worked as a researcher and statistics teacher at the Wageningen University and Research (Netherlands) for 38 years. His main fields of interest are sampling theory and geostatistics. He has gathered rich research experience in developing and applying statistical methods for natural resources inventory and monitoring. In 2015, he was appointed Adjunct Professor at Nanjing Normal University, Nanjing, China. He has published about 100 papers in peer-reviewed, international journals. He is second co-author of the book 'Sampling for Natural Resource Monitoring', published in 2006 by Springer. This book is widely acclaimed in soil, earth, environmental, agricultural and statistical science. Since January 1, 2022 he is retired and lives a joyful life in the countryside, where he grows vegetables in the garden, goes on cycling tours and sings in a choir. Every now and then, during rainy days, he works as a private contractor for the sole proprietorship Spatial Sampling registered with the Chamber of Commerce in the Netherlands.
"What makes this book different is the level of detail at which
sensitive issues on spatial sampling designs provided by the
specialized literature are discussed and the strong way in which
the author constructs his arguments. Dick J. Brus proposes a
valuable book, equally complex and accessible, a practical grounded
resource for researchers, master and doctoral students interested
in spatial sampling problems, sampling designs, and subsequent
inferences."
~Anca Vitcu, ISCB Book Reviews"The theory is accessible and well
presented. The book is rich in examples based on real applications,
and when discussing implementation, guidelines on which methods
could be more suited in terms of computing time are presented,
which can be useful. Additionally, exercises are provided at the
end of sections and of chapters, together with solutions at the end
of the book, which could be helpful if the book were used as
textbook. We think the strength of the book is surely the software
implementation part: accessible R code is
provided to replicate the examples, the scripts are freely
available on GitHub, and, more importantly, the code is well
explained, and functions and packages are described."~Francesco
Pantalone & Roberto Benedetti (11 Nov 2024), The American
Statistician
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