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Nonlinear Regression with R
- Coherent and unified treatment of nonlinear regression with R. - Example-based approach. - Wide area of application.
Allelopathy in Sustainable Agriculture and Forestry
This is the first comprehensive and up-to-date reference on the science, mechanism, methodology, and application of allelopathy. The objective of this practical reference is to report on the latest advances by inviting leading scientists to contribute in specific fields. The volume is organized under three major subsections: History of allelopathy, Allelochemicals, allelopathic mechanisms, and bioassays, and Application of allelopathy in agriculture and forestry.
Using R for Modelling and Quantitative Methods in Fisheries
Using R for Modelling and Quantitative Methods in Fisheries has evolved and been adapted from an earlier book by the same author and provides a detailed introduction to analytical methods commonly used by fishery scientists, ecologists, and advanced students using the open-source software R as a programming tool. Some knowledge of R is assumed, as this is a book about using R, but an introduction to the development and working of functions, and how one can explore the contents of R functions and packages, is provided. The example analyses proceed step-by-step using code listed in the book and from the book’s companion R package, MQMF, available from GitHub and the standard archive, CRAN. T...
R for Conservation and Development Projects
This book is aimed at conservation and development practitioners who need to learn and use R in a part-time professional context. It gives people with a non-technical background a set of skills to graph, map, and model in R. It also provides background on data integration in project management and covers fundamental statistical concepts. The book aims to demystify R and give practitioners the confidence to use it. Key Features: • Viewing data science as part of a greater knowledge and decision making system • Foundation sections on inference, evidence, and data integration • Plain English explanations of R functions • Relatable examples which are typical of activities undertaken by conservation and development organisations in the developing world • Worked examples showing how data analysis can be incorporated into project reports
Introduction to Environmental Management
Hardbound. This book provides a comprehensive survey of the various sub-disciplines which form the basis of environmental management. The book was written by experts in the three following categories: Natural Sciences topics such as soil, air and water pollution, water management, aspects of pesticides and gene technology; Social Sciences consisting of topics in countryside planning, environmental economics and law; and finally, subjects in Environmental Science and Ecology such as EIA and environmental management modelling are assessed. This volume is intended as an introductory overview of these topics and presents the tools required to practice environmental management. The book is expected to serve as a textbook and a reference book in teaching environmental management at a college or university level.
Gestion des mauvaises herbes pour les pays en développement
En 1994, la FAO publiait "Gestion des mauvaises herbes pour les pays en développement" afin de divulguer les informations les plus importantes concernant la gestion des mauvaises herbes. Le présent ouvrage présente la mise à jour de ces informations et les nouveaux développements en la matière. Il se compose de trois chapitres contenant des indications concernant la bioécologie des mauvaises herbes, les adventices à problèmes et le détail de différentes stratégies de lutte. Bien qu'aucune information ne soit fournie concernant les molécules des nouveaux herbicides, la résistance des herbicides et la manière de la gérer, ainsi que les risques et avantages des cultures transgéniques résistantes aux herbicides sont des sujets bien traités.
Dose-Response Analysis Using R
Nowadays the term dose-response is used in many different contexts and many different scientific disciplines including agriculture, biochemistry, chemistry, environmental sciences, genetics, pharmacology, plant sciences, toxicology, and zoology. In the 1940 and 1950s, dose-response analysis was intimately linked to evaluation of toxicity in terms of binary responses, such as immobility and mortality, with a limited number of doses of a toxic compound being compared to a control group (dose 0). Later, dose-response analysis has been extended to other types of data and to more complex experimental designs. Moreover, estimation of model parameters has undergone a dramatic change, from strugglin...
Bayesian Computation with R
There has been dramatic growth in the development and application of Bayesian inference in statistics. Berger (2000) documents the increase in Bayesian activity by the number of published research articles, the number of books,andtheextensivenumberofapplicationsofBayesianarticlesinapplied disciplines such as science and engineering. One reason for the dramatic growth in Bayesian modeling is the availab- ity of computational algorithms to compute the range of integrals that are necessary in a Bayesian posterior analysis. Due to the speed of modern c- puters, it is now possible to use the Bayesian paradigm to ?t very complex models that cannot be ?t by alternative frequentist methods. To ?t Ba...
