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Author: Lauri Mehtatalo
Publisher: CRC Press
ISBN: 1498711499
Category : Mathematics
Languages : en
Pages : 412
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Book Description
Biometry for Forestry and Environmental Data with Examples in R focuses on statistical methods that are widely applicable in forestry and environmental sciences, but it also includes material that is of wider interest. Features: · Describes the theory and applications of selected statistical methods and illustrates their use and basic concepts through examples with forestry and environmental data in R. · Rigorous but easily accessible presentation of the linear, nonlinear, generalized linear and multivariate models, and their mixed-effects counterparts. Chapters on tree size, tree taper, measurement errors, and forest experiments are also included. · Necessary statistical theory about random variables, estimation and prediction is included. The wide applicability of the linear prediction theory is emphasized. · The hands-on examples with implementations using R make it easier for non-statisticians to understand the concepts and apply the methods with their own data. Lot of additional material is available at www.biombook.org. The book is aimed at students and researchers in forestry and environmental studies, but it will also be of interest to statisticians and researchers in other fields as well.
Author: Lauri Mehtatalo
Publisher: CRC Press
ISBN: 1498711499
Category : Mathematics
Languages : en
Pages : 412
Get Book Here
Book Description
Biometry for Forestry and Environmental Data with Examples in R focuses on statistical methods that are widely applicable in forestry and environmental sciences, but it also includes material that is of wider interest. Features: · Describes the theory and applications of selected statistical methods and illustrates their use and basic concepts through examples with forestry and environmental data in R. · Rigorous but easily accessible presentation of the linear, nonlinear, generalized linear and multivariate models, and their mixed-effects counterparts. Chapters on tree size, tree taper, measurement errors, and forest experiments are also included. · Necessary statistical theory about random variables, estimation and prediction is included. The wide applicability of the linear prediction theory is emphasized. · The hands-on examples with implementations using R make it easier for non-statisticians to understand the concepts and apply the methods with their own data. Lot of additional material is available at www.biombook.org. The book is aimed at students and researchers in forestry and environmental studies, but it will also be of interest to statisticians and researchers in other fields as well.
Author: Carsten Dormann
Publisher: Springer Nature
ISBN: 3030550206
Category : Medical
Languages : en
Pages : 264
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Book Description
Environmental Data Analysis is an introductory statistics textbook for environmental science. It covers descriptive, inferential and predictive statistics, centred on the Generalized Linear Model. The key idea behind this book is to approach statistical analyses from the perspective of maximum likelihood, essentially treating most analyses as (multiple) regression problems. The reader will be introduced to statistical distributions early on, and will learn to deploy models suitable for the data at hand, which in environmental science are often not normally distributed. To make the initially steep learning curve more manageable, each statistical chapter is followed by a walk-through in a corresponding R-based how-to chapter, which reviews the theory and applies it to environmental data. In this way, a coherent and expandable foundation in parametric statistics is laid, which can be expanded in advanced courses.The content has been “field-tested” in several years of courses on statistics for Environmental Science, Geography and Forestry taught at the University of Freiburg.
Author: Nicholas Lange
Publisher: Wiley-Interscience
ISBN:
Category : Mathematics
Languages : en
Pages : 532
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Book Description
Features 21 case studies that illustrate commonly used approaches to answer scientific questions in such areas as biology, toxicology, clinical medicine, environmental hazards, agriculture, forestry and wildlife. Examples of statistical methods used in these case studies include linear regression, survival analysis, principle components, design of experiments, resampling and bootstrap. A disk containing the collective data sets will accompany the book.
Author: Anthonie van Laar
Publisher: Springer Science & Business Media
ISBN: 1402059914
Category : Technology & Engineering
Languages : en
Pages : 390
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Book Description
Van Laar and Akça’s popular text book, Forest Mensuration, was first published in 1997. Like that first edition, this modern update is based on extensive research, teaching and practical experience in both Europe, and the tropics and subtropics. However, it has also been extensively revised, and now includes chapters on remote sensing and the application of aerial photographs and satellite imagery. The book assumes no advanced knowledge of statistical methods, and combines practical techniques with important historical and disciplinary context. The result is a strong balance between a handbook and a valuable reference.
Author: Dale L. Zimmerman
Publisher: CRC Press
ISBN: 0429595093
Category : Mathematics
Languages : en
Pages : 400
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Book Description
Many applied researchers equate spatial statistics with prediction or mapping, but this book naturally extends linear models, which includes regression and ANOVA as pillars of applied statistics, to achieve a more comprehensive treatment of the analysis of spatially autocorrelated data. Spatial Linear Models for Environmental Data, aimed at students and professionals with a master’s level training in statistics, presents a unique, applied, and thorough treatment of spatial linear models within a statistics framework. Two subfields, one called geostatistics and the other called areal or lattice models, are extensively covered. Zimmerman and Ver Hoef present topics clearly, using many examples and simulation studies to illustrate ideas. By mimicking their examples and R code, readers will be able to fit spatial linear models to their data and draw proper scientific conclusions. Topics covered include: Exploratory methods for spatial data including outlier detection, (semi)variograms, Moran’s I, and Geary’s c. Ordinary and generalized least squares regression methods and their application to spatial data. Suitable parametric models for the mean and covariance structure of geostatistical and areal data. Model-fitting, including inference methods for explanatory variables and likelihood-based methods for covariance parameters. Practical use of spatial linear models including prediction (kriging), spatial sampling, and spatial design of experiments for solving real world problems. All concepts are introduced in a natural order and illustrated throughout the book using four datasets. All analyses, tables, and figures are completely reproducible using open-source R code provided at a GitHub site. Exercises are given at the end of each chapter, with full solutions provided on an instructor’s FTP site supplied by the publisher.
Author: John A. Kershaw, Jr.
Publisher: John Wiley & Sons
ISBN: 1118902033
Category : Science
Languages : en
Pages : 650
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Book Description
Forest mensuration – the science of measurement applied to forest vegetation and forest products – holds value for basic ecology as well as sustainable forest management. As demands on the world’s forests have grown, scientists and professionals are increasingly called on to quantify forest composition, structure, and the goods and services forests provide. Grounded in geometry, sampling theory, and ecology as well as practical field experience, forest mensuration offers opportunities for creative problem solving and critical thinking. This fifth edition of the classic volume, Forest Mensuration, includes coverage of traditional and emerging topics, with attention to SI and Imperial units throughout. The book has been reorganised from the fourth edition to better integrate non-timber and ecological aspects of forest mensuration at the tree, stand, forest, and landscape scales throughout. The new edition includes new chapters that specifically address the integration of remotely sensed data in the forest inventory process, and inventory methods for dead and downed wood. One unifying theme, not only for traditional forestry but for the non-timber inventory and for remote sensing, is the use of covariates to make sampling more efficient and spatially explicit. This is introduced in the introductory chapter on statistics and the chapter on sampling designs has been restructured to highlight this approach and lay the foundation for further learning. New examples will be developed throughout the textbook with an emphasis on current issues and international practice. Students in applied forestry programs will find ample coverage of forest products and timber inventory, while expanded material on biodiversity, biomass and carbon inventory, downed dead wood, and the growing role of remote sensing in forest assessment will be valuable to a broader audience in applied ecology.
Author: Girish Chandra
Publisher: Springer Nature
ISBN: 9811514763
Category : Medical
Languages : en
Pages : 290
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Book Description
This book presents recent developments in statistical methodologies with particular relevance to applications in forestry and environmental sciences. It discusses important methodologies like ranked set sampling, adaptive cluster sampling, small area estimation, calibration approach-based estimators, design of experiments, multivariate techniques, Internet of Things, and ridge regression methods. It also covers the history of the implementation of statistical techniques in Indian forestry and the National Forest Inventory of India. The book is a valuable resource for applied statisticians, students, researchers, and practitioners in the forestry and environment sector. It includes real-world examples and case studies to help readers apply the techniques discussed. It also motivates academicians and researchers to use new technologies in the areas of forestry and environmental sciences with the help of software like R, MATLAB, Statistica, and Mathematica.
Author: Michail Prodan
Publisher: Elsevier
ISBN: 1483156559
Category : Mathematics
Languages : en
Pages : 461
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Book Description
Forest Biometrics presents the methods of mathematical statistics and biometrics that are significant to forestry. This book explores other fields related to forestry, which are explained with the help of a large number of practical examples. Organized into 25 chapters, this book starts with an overview of the variety of data that play a significant role in forest management, including the age of trees, the damage caused by storms, the fluctuation of timber prices, bark beetle infestation, and timber volume. This text then examines the factors that are responsible for a random distribution of the values in biological experimentation. Other chapters consider the important advantages of sample surveys compared to complete enumerations, include cheaper samples, wider applicability, quick results, and greater accuracy. The final chapter deals with the factors to be considered in determining the best time for harvesting of timber. This book is a valuable resource for students, research project leaders, and practical workers.
Author: Nicholas Polunin
Publisher: Earthscan
ISBN: 9781853833779
Category : Biography & Autobiography
Languages : en
Pages : 608
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Book Description
Full addresses with telephone and fax numbers are provided. Cross-referenced indexes list entrants by speciality and by country or major state, so that users can readily identify individuals in any given field and in any geographical location.
Author: Susan R. Wilson
Publisher: EOLSS Publications
ISBN: 1905839375
Category : Mathematics
Languages : en
Pages : 466
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Book Description
Biometrics is a component of Encyclopedia of Mathematical Sciences in the global Encyclopedia of Life Support Systems (EOLSS), which is an integrated compendium of twenty one Encyclopedias. Biometry is a broad discipline covering all applications of statistics and mathematics to biology. The Theme Biometrics is divided into areas of expertise essential for a proper application of statistical and mathematical methods to contemporary biological problems. These volumes cover four main topics: Data Collection and Analysis, Statistical Methodology, Computation, Biostatistical Methods and Research Design and Selected Topics. These volumes are aimed at the following five major target audiences: University and College students Educators, Professional practitioners, Research personnel and Policy analysts, managers, and decision makers and NGOs.
