Computer Graphics


Book Description

This book is an extensive treatise on the most up-to-date advances in computer graphics technology and its applications. Both in business and industrial areas as well as in research and development, you will see in this book an incredible devel opment of new methods and tools for computer graphics. They play essential roles in enhancing the productivity and quality of human work through computer graph ics and applications. Extensive coverage of the diverse world of computer graphics is the privilege of this book, which is the Proceedings of InterGraphics '83. This was a truly interna tional computer graphics conference and exhibit, held in Tokyo, April 11-14, 1983, sponsored by the World Computer Grpphics Association (WCGA) and organized by the Japan Management Association (JMA) in coopera'tion' with ·~CM-SIGGRAPH. InterGraphics has over 15 thousands participants. This book consists of seven Chapters. The first two chapters are on the basics of computer graphics, and the remaining five chapters are dedicated to typical appli cation areas of computer graphics. Chapter 1 contains four papers on "graphics techniques". Techniques to generate jag free images, to simulate digital logic, to display free surfaces and to interact with 3 dimensional (3D) shaded graphics are presented. Chapter 2 covers "graphics standards and 3D models" in five papers. Two papers discuss the CORE standard and the GKS standard. Three papers de scribe various 3D models and their evaluations.







Linne & Ringsrud's Clinical Laboratory Science - E-Book


Book Description

Updated and easy-to-use, Linne & Ringsrud's Clinical Laboratory Science: The Basics and Routine Techniques, 6th Edition delivers a fundamental overview of the laboratory skills and techniques essential for success in your classes and your career. Author Mary Louise Turgeon's simple, straightforward writing clarifies complex concepts, and a discipline-by-discipline approach helps you build the knowledge to confidently perform clinical laboratory tests and ensure accurate, effective results. Expert insight from respected educator and author Mary Louise Turgeon reflects the full spectrum of clinical laboratory science. Engaging full-color design and illustrations familiarize you with what you'll see under the microscope. Streamlined approach makes must-know concepts and practices more accessible. Broad scope provides an ideal introduction to clinical laboratory science at various levels, including MLS/MLT and Medical Assisting. Hands-on procedures guide you through the exact steps you'll perform in the lab. Learning objectives help you identify key chapter content and study more effectively. Case studies challenge you to apply concepts to realistic scenarios. Review questions at the end of each chapter help you assess your understanding and identify areas requiring additional study. A companion Evolve website provides convenient online access to procedures, glossary, audio glossary and links to additional information. Updated instrumentation coverage familiarizes you with the latest technological advancements in clinical laboratory science. Perforated pages make it easy for you to take procedure instructions with you into the lab. Enhanced organization helps you study more efficiently and quickly locate the information you need. Convenient glossary provides fast, easy access to definitions of key terms.




Applied Survival Analysis Using R


Book Description

Applied Survival Analysis Using R covers the main principles of survival analysis, gives examples of how it is applied, and teaches how to put those principles to use to analyze data using R as a vehicle. Survival data, where the primary outcome is time to a specific event, arise in many areas of biomedical research, including clinical trials, epidemiological studies, and studies of animals. Many survival methods are extensions of techniques used in linear regression and categorical data, while other aspects of this field are unique to survival data. This text employs numerous actual examples to illustrate survival curve estimation, comparison of survivals of different groups, proper accounting for censoring and truncation, model variable selection, and residual analysis. Because explaining survival analysis requires more advanced mathematics than many other statistical topics, this book is organized with basic concepts and most frequently used procedures covered in earlier chapters, with more advanced topics near the end and in the appendices. A background in basic linear regression and categorical data analysis, as well as a basic knowledge of calculus and the R system, will help the reader to fully appreciate the information presented. Examples are simple and straightforward while still illustrating key points, shedding light on the application of survival analysis in a way that is useful for graduate students, researchers, and practitioners in biostatistics.




Bayesian Data Analysis, Third Edition


Book Description

Now in its third edition, this classic book is widely considered the leading text on Bayesian methods, lauded for its accessible, practical approach to analyzing data and solving research problems. Bayesian Data Analysis, Third Edition continues to take an applied approach to analysis using up-to-date Bayesian methods. The authors—all leaders in the statistics community—introduce basic concepts from a data-analytic perspective before presenting advanced methods. Throughout the text, numerous worked examples drawn from real applications and research emphasize the use of Bayesian inference in practice. New to the Third Edition Four new chapters on nonparametric modeling Coverage of weakly informative priors and boundary-avoiding priors Updated discussion of cross-validation and predictive information criteria Improved convergence monitoring and effective sample size calculations for iterative simulation Presentations of Hamiltonian Monte Carlo, variational Bayes, and expectation propagation New and revised software code The book can be used in three different ways. For undergraduate students, it introduces Bayesian inference starting from first principles. For graduate students, the text presents effective current approaches to Bayesian modeling and computation in statistics and related fields. For researchers, it provides an assortment of Bayesian methods in applied statistics. Additional materials, including data sets used in the examples, solutions to selected exercises, and software instructions, are available on the book’s web page.




Accounting


Book Description

Accounting, 9th Edition continues the strong reputation established by this leading Australian text as the most comprehensive book for students studying introductory accounting in undergraduate or postgraduate programs. The full-colour design provides students with a reader-friendly text to enhance their understanding of concepts and make their study more enjoyable. The text builds on the thorough and reliable explanation of the accounting process through the 'Business knowledge' chapter vignettes that apply the principles to practice. Previous editions were renowned for the number of exercises and problems, and the new edition builds on this superior teaching feature. The end-of-chapter activities are designed to encourage student con dence through the development of skills in decision making, critical thinking, ethical thinking, analysis and communication. Want to Succeed in Accounting? WileyPLUS is a powerful online system packed with features to help you make the most of your potential and achieve the best results you can! With WileyPLUS you get: - a complete online version of your text and other study resources - problem-solving help, instant grading and feedback on activities - ability to track your progress and results during the semester.




The Birnbaum-Saunders Distribution


Book Description

The Birnbaum-Saunders Distribution presents the statistical theory, methodology, and applications of the Birnbaum-Saunders distribution, a very flexible distribution for modeling different types of data (mainly lifetime data). The book describes the most recent theoretical developments of this model, including properties, transformations and related distributions, lifetime analysis, and shape analysis. It discusses methods of inference based on uncensored and censored data, goodness-of-fit tests, and random number generation algorithms for the Birnbaum-Saunders distribution, also presenting existing and future applications. - Introduces inference in the Birnbaum-Saunders distribution - Provides a comprehensive review of the statistical theory and methodology of the Birnbaum-Distribution - Discusses different applications of the Birnbaum-Saunders distribution - Explains characterization and the lifetime analysis




Applied Econometrics with R


Book Description

R is a language and environment for data analysis and graphics. It may be considered an implementation of S, an award-winning language initially - veloped at Bell Laboratories since the late 1970s. The R project was initiated by Robert Gentleman and Ross Ihaka at the University of Auckland, New Zealand, in the early 1990s, and has been developed by an international team since mid-1997. Historically, econometricians have favored other computing environments, some of which have fallen by the wayside, and also a variety of packages with canned routines. We believe that R has great potential in econometrics, both for research and for teaching. There are at least three reasons for this: (1) R is mostly platform independent and runs on Microsoft Windows, the Mac family of operating systems, and various ?avors of Unix/Linux, and also on some more exotic platforms. (2) R is free software that can be downloaded and installed at no cost from a family of mirror sites around the globe, the Comprehensive R Archive Network (CRAN); hence students can easily install it on their own machines. (3) R is open-source software, so that the full source code is available and can be inspected to understand what it really does, learn from it, and modify and extend it. We also like to think that platform independence and the open-source philosophy make R an ideal environment for reproducible econometric research.




Accounting Trends and Techniques: U.S. GAAP Financial Statements--Best Practices in Presentation and Disclosure


Book Description

Updated for new accounting and auditing guidance issued, this valuable tool provides hundreds of high quality disclosure examples from carefully selected U.S. companies of different sizes, across industries such as banking, credit and insurance, communication services, and healthcare from such organizations as Scotts Miracle-Gro, Coca-Cola, Caterpillar, and BB&T. Illustrations of the most important, immediate, and challenging disclosures, such as derivatives and hedging, consolidations, and fair value measurement are provided. Hot topics include statement of cash flows, going concern, and business combinations and intangibles. This edition also provides clear, direct guidance to help you understand and comply with all significant reporting requirements and detailed indexes to help you quickly find exactly what you need.




Applied Logistic Regression


Book Description

From the reviews of the First Edition. "An interesting, useful, and well-written book on logistic regression models . . . Hosmer and Lemeshow have used very little mathematics, have presented difficult concepts heuristically and through illustrative examples, and have included references." —Choice "Well written, clearly organized, and comprehensive . . . the authors carefully walk the reader through the estimation of interpretation of coefficients from a wide variety of logistic regression models . . . their careful explication of the quantitative re-expression of coefficients from these various models is excellent." —Contemporary Sociology "An extremely well-written book that will certainly prove an invaluable acquisition to the practicing statistician who finds other literature on analysis of discrete data hard to follow or heavily theoretical." —The Statistician In this revised and updated edition of their popular book, David Hosmer and Stanley Lemeshow continue to provide an amazingly accessible introduction to the logistic regression model while incorporating advances of the last decade, including a variety of software packages for the analysis of data sets. Hosmer and Lemeshow extend the discussion from biostatistics and epidemiology to cutting-edge applications in data mining and machine learning, guiding readers step-by-step through the use of modeling techniques for dichotomous data in diverse fields. Ample new topics and expanded discussions of existing material are accompanied by a wealth of real-world examples-with extensive data sets available over the Internet.