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Author: Richard E. Plant Publisher: CRC Press ISBN: 1439819149 Category : Mathematics Languages : en Pages : 637
Book Description
Assuming no prior knowledge of R, Spatial Data Analysis in Ecology and Agriculture Using R provides practical instruction on the use of the R programming language to analyze spatial data arising from research in ecology and agriculture. Written in terms of four data sets easily accessible online, this book guides the reader through the analysis of each data set, including setting research objectives, designing the sampling plan, data quality control, exploratory and confirmatory data analysis, and drawing scientific conclusions. Based on the author’s spatial data analysis course at the University of California, Davis, the book is intended for classroom use or self-study by graduate students and researchers in ecology, geography, and agricultural science with an interest in the analysis of spatial data.
Author: Richard E. Plant Publisher: CRC Press ISBN: 1439819149 Category : Mathematics Languages : en Pages : 637
Book Description
Assuming no prior knowledge of R, Spatial Data Analysis in Ecology and Agriculture Using R provides practical instruction on the use of the R programming language to analyze spatial data arising from research in ecology and agriculture. Written in terms of four data sets easily accessible online, this book guides the reader through the analysis of each data set, including setting research objectives, designing the sampling plan, data quality control, exploratory and confirmatory data analysis, and drawing scientific conclusions. Based on the author’s spatial data analysis course at the University of California, Davis, the book is intended for classroom use or self-study by graduate students and researchers in ecology, geography, and agricultural science with an interest in the analysis of spatial data.
Author: Guy Lebanon Publisher: Springer ISBN: 3319981498 Category : Computers Languages : en Pages : 584
Book Description
This book introduces basic computing skills designed for industry professionals without a strong computer science background. Written in an easily accessible manner, and accompanied by a user-friendly website, it serves as a self-study guide to survey data science and data engineering for those who aspire to start a computing career, or expand on their current roles, in areas such as applied statistics, big data, machine learning, data mining, and informatics. The authors draw from their combined experience working at software and social network companies, on big data products at several major online retailers, as well as their experience building big data systems for an AI startup. Spanning from the basic inner workings of a computer to advanced data manipulation techniques, this book opens doors for readers to quickly explore and enhance their computing knowledge. Computing with Data comprises a wide range of computational topics essential for data scientists, analysts, and engineers, providing them with the necessary tools to be successful in any role that involves computing with data. The introduction is self-contained, and chapters progress from basic hardware concepts to operating systems, programming languages, graphing and processing data, testing and programming tools, big data frameworks, and cloud computing. The book is fashioned with several audiences in mind. Readers without a strong educational background in CS--or those who need a refresher--will find the chapters on hardware, operating systems, and programming languages particularly useful. Readers with a strong educational background in CS, but without significant industry background, will find the following chapters especially beneficial: learning R, testing, programming, visualizing and processing data in Python and R, system design for big data, data stores, and software craftsmanship.
Author: Ronald J. Tallarida Publisher: Springer Science & Business Media ISBN: 1461249740 Category : Medical Languages : en Pages : 305
Book Description
This book contains a collection of quantitative procedures in common use in pharmacology and related disciplines. It is intended for students and researchers in all fields who work with drugs. Many physicians, especially those concerned with clinical pharmacology, will also find much that is useful. The procedures included may be considered "core" since they are generally applicable to all classes of drugs. Some of the procedures deal with statistics and, hence, have even wider application. In this new edition we have increased the number of procedures from 33 (in the first edition) to 48. Other procedures have been revised and expanded. Yet the basic philosophy of this new edition remains unchanged from the first. That is, the pharmacologic basis of each procedure is presented, along with the necessary formulas and one or more worked examples. An associated computer program is included for each procedure and its use is illustrated with the same worked example used in the text. The discussions of theory and the sample computations are brief and self-contained, so that all computations can be made with the aid of a pocket calculator and the statistical tables contained in Appendix A. Yet it is realized that the proliferation of lower-priced microcom puters is likely to mean that more and more readers will utilize a computer for most calculations. Accordingly, we have modified the format of the book to facilitate computer usage.
Author: Ottar N. Bjørnstad Publisher: Springer Nature ISBN: 3031120566 Category : Medical Languages : en Pages : 386
Book Description
This book is designed to be a practical study in infectious disease dynamics. It offers an easy-to-follow implementation and analysis of mathematical epidemiology. It focuses on recent case studies in order to explore various conceptual, mathematical, and statistical issues. The dynamics of infectious diseases shows a wide diversity of pattern. Some have locally persistent chains-of-transmission, others persist spatially in consumer-resource metapopulations. Some infections are prevalent among the young, some among the old and some are age-invariant. Temporally, some diseases have little variation in prevalence, some have predictable seasonal shifts and others exhibit violent epidemics that may be regular or irregular in their timing. Models and ‘models-with-data’ have proved invaluable for understanding and predicting this diversity, and thence help improve intervention and control. Using mathematical models to understand infectious disease, dynamics has a very rich history in epidemiology. The field has seen broad expansions of theories as well as a surge in real-life application of mathematics to dynamics and control of infectious disease. The chapters of Epidemics: Models and Data Using R have been organized as follows: chapters 1-10 is a mix and match of models, data and statistics pertaining to local disease dynamics; chapters 11-13 pertains to spatial and spatiotemporal dynamics; chapter 14 highlights similarities between the dynamics of infectious disease and parasitoid-host dynamics; Finally, chapters 15 and 16 overview additional statistical methodology useful in studies of infectious disease dynamics. This book can be used as a guide for working with data, models and ‘models-and-data’ to understand epidemics and infectious disease dynamics in space and time. All the code and data sets are distributed in the epimdr2 R package to facilitate the hands-on philosophy of the text.
Author: Richard E. Plant
Author: Richard E. Plant
Author: Guy Lebanon
Author: Ronald J. Tallarida
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Author: 
Author: Joseph A. Kaplan
Author: United States. National Aeronautics and Space Administration
Author: James J. Lichtenberg
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Author: Ottar N. Bjørnstad