Brus dick j (39 risultati)

Condizione: New. pages cm.

Condizione: New.

UNK. Condizione: New. New Book. Shipped from UK. Established seller since 2000.

UNK. Condizione: New. New Book. Shipped from UK. Established seller since 2000.

Condizione: New. pages cm First edition Includes bibliographical references and index.

Condizione: New. pages cm.

Paperback. Condizione: Brand New. 548 pages. 6.14x1.24x9.21 inches. In Stock.

Condizione: New. 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 develop.

Condizione: New.

Condizione: New.

Condizione: As New. Unread book in perfect condition.

Taschenbuch. Condizione: Neu. Neuware - Scientific research often starts with data collection. However, many researchers pay insufficient attention to this first step in their research. The author, researcher at Wageningen University and Research, often had to conclude that the data collected by fellow researchers were suboptimal, or in some cases even unsuitable for their aim. One reason is that sampling is frequently overlooked in statistics courses. Another reason is the lack of practical textbooks on sampling. Numerous books have been published on the statistical analysis and modelling of data using R, but to date no book has been published in this series on how these data can best be collected. This book fills this gap. Spatial Sampling with R presents an overview of sampling designs for spatial sample survey and monitoring. It shows how to implement the sampling designs and how to estimate (sub)population- and space-time parameters in R.Key features - Describes classical, basic sampling designs for spatial survey, as well as recently developed, advanced sampling designs and estimators - Presents probability sampling designs for estimating parameters for a (sub)population, as well as non-probability sampling designs for mapping - Gives comprehensive overview of model-assisted estimators - Covers Bayesian approach to sampling design - Illustrates sampling designs with surveys of soil organic carbon, above-ground biomass, air temperature, opium poppy - Explains integration of wall-to-wall data sets (e.g. remote sensing images) and sample data - Data and R code available on github - Exercises added making the book suitable as a textbook for students The target group of this book are researchers and practitioners of sample surveys, as well as students in environmental, ecological, agricultural science or any other science in which knowledge about a population of interest is collected through spatial sampling. This book helps to implement proper sampling designs, tailored to their problems at hand, so that valuable data are collected that can be used to answer the research questions.…

Condizione: As New. Unread book in perfect condition.

Condizione: New.

Condizione: New. 1st edition NO-PA16APR2015-KAP.

Condizione: New.

Condizione: New. In English.

Hardback. Condizione: New. New copy - Usually dispatched within 4 working days.

Condizione: New. In English.

Condizione: New.

Condizione: New.

Condizione: New.

Condizione: New. In English.

Hardback. Condizione: New. Scientific research often starts with data collection. However, many researchers pay insufficient attention to this first step in their research. The author, researcher at Wageningen University and Research, often had to conclude that the data collected by fellow researchers were suboptimal, or in some cases even unsuitable for their aim. One reason is that sampling is frequently overlooked in statistics courses. Another reason is the lack of practical textbooks on sampling. Numerous books have been published on the statistical analysis and modelling of data using R, but to date no book has been published in this series on how these data can best be collected. This book fills this gap. Spatial Sampling with R presents an overview of sampling designs for spatial sample survey and monitoring. It shows how to implement the sampling designs and how to estimate (sub)population- and space-time parameters in R.Key featuresDescribes classical, basic sampling designs for spatial survey, as well as recently developed, advanced sampling designs and estimatorsPresents probability sampling designs for estimating parameters for a (sub)population, as well as non-probability sampling designs for mappingGives comprehensive overview of model-assisted estimatorsCovers Bayesian approach to sampling designIllustrates sampling designs with surveys of soil organic carbon, above-ground biomass, air temperature, opium poppyExplains integration of wall-to-wall data sets (e.g. remote sensing images) and sample dataData and R code available on githubExercises added making the book suitable as a textbook for studentsThe target group of this book are researchers and practitioners of sample surveys, as well as students in environmental, ecological, agricultural science or any other science in which knowledge about a population of interest is collected through spatial sampling. This book helps to implement proper sampling designs, tailored to their problems at hand, so that valuable data are collected that can be used to answer the research questions.…

hardcover. Condizione: New. In shrink wrap. Looks like an interesting title.

Condizione: As New. Unread book in perfect condition.

Hardcover. Condizione: Brand New. 534 pages. 9.25x6.25x1.25 inches. In Stock.

Condizione: As New. Unread book in perfect condition.

Hardback. Condizione: New. Scientific research often starts with data collection. However, many researchers pay insufficient attention to this first step in their research. The author, researcher at Wageningen University and Research, often had to conclude that the data collected by fellow researchers were suboptimal, or in some cases even unsuitable for their aim. One reason is that sampling is frequently overlooked in statistics courses. Another reason is the lack of practical textbooks on sampling. Numerous books have been published on the statistical analysis and modelling of data using R, but to date no book has been published in this series on how these data can best be collected. This book fills this gap. Spatial Sampling with R presents an overview of sampling designs for spatial sample survey and monitoring. It shows how to implement the sampling designs and how to estimate (sub)population- and space-time parameters in R.Key featuresDescribes classical, basic sampling designs for spatial survey, as well as recently developed, advanced sampling designs and estimatorsPresents probability sampling designs for estimating parameters for a (sub)population, as well as non-probability sampling designs for mappingGives comprehensive overview of model-assisted estimatorsCovers Bayesian approach to sampling designIllustrates sampling designs with surveys of soil organic carbon, above-ground biomass, air temperature, opium poppyExplains integration of wall-to-wall data sets (e.g. remote sensing images) and sample dataData and R code available on githubExercises added making the book suitable as a textbook for studentsThe target group of this book are researchers and practitioners of sample surveys, as well as students in environmental, ecological, agricultural science or any other science in which knowledge about a population of interest is collected through spatial sampling. This book helps to implement proper sampling designs, tailored to their problems at hand, so that valuable data are collected that can be used to answer the research questions.…

Paperback. Condizione: new. Paperback. Scientific research often starts with data collection. However, many researchers pay insufficient attention to this first step in their research. The author, researcher at Wageningen University and Research, often had to conclude that the data collected by fellow researchers were suboptimal, or in some cases even unsuitable for their aim. One reason is that sampling is frequently overlooked in statistics courses. Another reason is the lack of practical textbooks on sampling. Numerous books have been published on the statistical analysis and modelling of data using R, but to date no book has been published in this series on how these data can best be collected. This book fills this gap. Spatial Sampling with R presents an overview of sampling designs for spatial sample survey and monitoring. It shows how to implement the sampling designs and how to estimate (sub)population- and space-time parameters in R.Key featuresDescribes classical, basic sampling designs for spatial survey, as well as recently developed, advanced sampling designs and estimatorsPresents probability sampling designs for estimating parameters for a (sub)population, as well as non-probability sampling designs for mappingGives comprehensive overview of model-assisted estimatorsCovers Bayesian approach to sampling designIllustrates sampling designs with surveys of soil organic carbon, above-ground biomass, air temperature, opium poppyExplains integration of wall-to-wall data sets (e.g. remote sensing images) and sample dataData and R code available on githubExercises added making the book suitable as a textbook for studentsThe target group of this book are researchers and practitioners of sample surveys, as well as students in environmental, ecological, agricultural science or any other science in which knowledge about a population of interest is collected through spatial sampling. This book helps to implement proper sampling designs, tailored to their problems at hand, so that valuable data are collected that can be used to answer the research questions. Scientific research often starts with data collection. However, many researchers pay insufficient attention to this first step in their research. The author, researcher at Wageningen University and Research, often had to conclude that the data collected by fellow researchers were suboptimal, or in some cases even unsuitable for their aim. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.…