Forest Analytics with R - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Forest Analytics with R write by Andrew P. Robinson. This book was released on 2010-11-05. Forest Analytics with R available in PDF, EPUB and Kindle. Forest Analytics with R combines practical, down-to-earth forestry data analysis and solutions to real forest management challenges with state-of-the-art statistical and data-handling functionality. The authors adopt a problem-driven approach, in which statistical and mathematical tools are introduced in the context of the forestry problem that they can help to resolve. All the tools are introduced in the context of real forestry datasets, which provide compelling examples of practical applications. The modeling challenges covered within the book include imputation and interpolation for spatial data, fitting probability density functions to tree measurement data using maximum likelihood, fitting allometric functions using both linear and non-linear least-squares regression, and fitting growth models using both linear and non-linear mixed-effects modeling. The coverage also includes deploying and using forest growth models written in compiled languages, analysis of natural resources and forestry inventory data, and forest estate planning and optimization using linear programming. The book would be ideal for a one-semester class in forest biometrics or applied statistics for natural resources management. The text assumes no programming background, some introductory statistics, and very basic applied mathematics.
Doing Meta-Analysis with R
Doing Meta-Analysis with R - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Doing Meta-Analysis with R write by Mathias Harrer. This book was released on 2021-09-15. Doing Meta-Analysis with R available in PDF, EPUB and Kindle. Doing Meta-Analysis with R: A Hands-On Guide serves as an accessible introduction on how meta-analyses can be conducted in R. Essential steps for meta-analysis are covered, including calculation and pooling of outcome measures, forest plots, heterogeneity diagnostics, subgroup analyses, meta-regression, methods to control for publication bias, risk of bias assessments and plotting tools. Advanced but highly relevant topics such as network meta-analysis, multi-three-level meta-analyses, Bayesian meta-analysis approaches and SEM meta-analysis are also covered. A companion R package, dmetar, is introduced at the beginning of the guide. It contains data sets and several helper functions for the meta and metafor package used in the guide. The programming and statistical background covered in the book are kept at a non-expert level, making the book widely accessible. Features • Contains two introductory chapters on how to set up an R environment and do basic imports/manipulations of meta-analysis data, including exercises • Describes statistical concepts clearly and concisely before applying them in R • Includes step-by-step guidance through the coding required to perform meta-analyses, and a companion R package for the book
Biometry for Forestry and Environmental Data
Biometry for Forestry and Environmental Data - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Biometry for Forestry and Environmental Data write by Lauri Mehtatalo. This book was released on 2020-05-27. Biometry for Forestry and Environmental Data available in PDF, EPUB and Kindle. 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.
Data Science in Education Using R
Data Science in Education Using R - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Data Science in Education Using R write by Ryan A. Estrellado. This book was released on 2020-10-26. Data Science in Education Using R available in PDF, EPUB and Kindle. Data Science in Education Using R is the go-to reference for learning data science in the education field. The book answers questions like: What does a data scientist in education do? How do I get started learning R, the popular open-source statistical programming language? And what does a data analysis project in education look like? If you’re just getting started with R in an education job, this is the book you’ll want with you. This book gets you started with R by teaching the building blocks of programming that you’ll use many times in your career. The book takes a "learn by doing" approach and offers eight analysis walkthroughs that show you a data analysis from start to finish, complete with code for you to practice with. The book finishes with how to get involved in the data science community and how to integrate data science in your education job. This book will be an essential resource for education professionals and researchers looking to increase their data analysis skills as part of their professional and academic development.
The R Book
The R Book - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook The R Book write by Michael J. Crawley. This book was released on 2007-06-13. The R Book available in PDF, EPUB and Kindle. The high-level language of R is recognized as one of the mostpowerful and flexible statistical software environments, and israpidly becoming the standard setting for quantitative analysis,statistics and graphics. R provides free access to unrivalledcoverage and cutting-edge applications, enabling the user to applynumerous statistical methods ranging from simple regression to timeseries or multivariate analysis. Building on the success of the author’s bestsellingStatistics: An Introduction using R, The R Book ispacked with worked examples, providing an all inclusive guide to R,ideal for novice and more accomplished users alike. The bookassumes no background in statistics or computing and introduces theadvantages of the R environment, detailing its applications in awide range of disciplines. Provides the first comprehensive reference manual for the Rlanguage, including practical guidance and full coverage of thegraphics facilities. Introduces all the statistical models covered by R, beginningwith simple classical tests such as chi-square and t-test. Proceeds to examine more advance methods, from regression andanalysis of variance, through to generalized linear models,generalized mixed models, time series, spatial statistics,multivariate statistics and much more. The R Book is aimed at undergraduates, postgraduates andprofessionals in science, engineering and medicine. It is alsoideal for students and professionals in statistics, economics,geography and the social sciences.
