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Statistical data are not always precise numbers, or vectors, or categories. Real data are frequently what is called fuzzy. Examples where this fuzziness is obvious are quality of life data, environmental, biological, medical, sociological and economics data. Also the results of measurements can be best described by using fuzzy numbers and fuzzy vectors respectively. Statistical analysis methods have to be adapted for the analysis of fuzzy data. In this book, the foundations of the description of fuzzy data are explained, including methods on how to obtain the characterizing function of fuzzy measurement results. Furthermore, statistical methods are then generalized to the analysis of fuzzy data and fuzzy a-priori information. Key Features: Provides basic methods for the mathematical description of fuzzy data, as well as statistical methods that can be used to analyze fuzzy data. Describes methods of increasing importance with applications in areas such as environmental statistics and social science. Complements the theory with exercises and solutions and is illustrated throughout with diagrams and examples. Explores areas such quantitative description of data uncertainty and mathematical description of fuzzy data. This work is aimed at statisticians working with fuzzy logic, engineering statisticians, finance researchers, and environmental statisticians. It is written for readers who are familiar with elementary stochastic models and basic statistical methods.
Statistical pattern recognition relates to the use of statistical techniques for analysing data measurements in order to extract information and make justified decisions. It is a very active area of study and research, which has seen many advances in recent years. Applications such as data mining, web searching, multimedia data retrieval, face recognition, and cursive handwriting recognition, all require robust and efficient pattern recognition techniques. This third edition provides an introduction to statistical pattern theory and techniques, with material drawn from a wide range of fields, including the areas of engineering, statistics, computer science and the social sciences. The book has been updated to cover new methods and applications, and includes a wide range of techniques such as Bayesian methods, neural networks, support vector machines, feature selection and feature reduction techniques.Technical descriptions and motivations are provided, and the techniques are illustrated using real examples. Statistical Pattern Recognition, 3rd Edition: Provides a self-contained introduction to statistical pattern recognition. Includes new material presenting the analysis of complex networks. Introduces readers to methods for Bayesian density estimation. Presents descriptions of new applications in biometrics, security, finance and condition monitoring. Provides descriptions and guidance for implementing techniques, which will be invaluable to software engineers and developers seeking to develop real applications Describes mathematically the range of statistical pattern recognition techniques. Presents a variety of exercises including more extensive computer projects. The in-depth technical descriptions make the book suitable for senior undergraduate and graduate students in statistics, computer science and engineering. Statistical Pattern Recognition is also an excellent reference source for technical professionals. Chapters have been arranged to facilitate implementation of the techniques by software engineers and developers in non-statistical engineering fields. www.wiley.com/go/statistical_pattern_recognition
In the real world, there are numerous and various events that occur on and alongside networks, including the occurrence of traffic accidents on highways, the location of stores alongside roads, the incidence of crime on streets and the contamination along rivers. In order to carry out analyses of those events, the researcher needs to be familiar with a range of specific techniques. Spatial Analysis Along Networks provides a practical guide to the necessary statistical techniques and their computational implementation. Each chapter illustrates a specific technique, from Stochastic Point Processes on a Network and Network Voronoi Diagrams, to Network K-function and Point Density Estimation Methods, and the Network Huff Model. The authors also discuss and illustrate the undertaking of the statistical tests described in a Geographical Information System (GIS) environment as well as demonstrating the user-friendly free software package SANET. Spatial Analysis Along Networks: Presents a much-needed practical guide to statistical spatial analysis of events on and alongside a network, in a logical, user-friendly order. Introduces the preliminary methods involved, before detailing the advanced, computational methods, enabling the readers a complete understanding of the advanced topics. Dedicates a separate chapter to each of the major techniques involved. Demonstrates the practicalities of undertaking the tests described in the book, using a GIS. Is supported by a supplementary website, providing readers with a link to the free software package SANET, so they can execute the statistical methods described in the book. Students and researchers studying spatial statistics, spatial analysis, geography, GIS, OR, traffic accident analysis, criminology, retail marketing, facility management and ecology will benefit from this book.
A comprehensive introduction to sampling-based methods in statistical computing The use of computers in mathematics and statistics has opened up a wide range of techniques for studying otherwise intractable problems. Sampling-based simulation techniques are now an invaluable tool for exploring statistical models. This book gives a comprehensive introduction to the exciting area of sampling-based methods. An Introduction to Statistical Computing introduces the classical topics of random number generation and Monte Carlo methods. It also includes some advanced methods such as the reversible jump Markov chain Monte Carlo algorithm and modern methods such as approximate Bayesian computation and multilevel Monte Carlo techniques An Introduction to Statistical Computing: Fully covers the traditional topics of statistical computing. Discusses both practical aspects and the theoretical background. Includes a chapter about continuous-time models. Illustrates all methods using examples and exercises. Provides answers to the exercises (using the statistical computing environment R); the corresponding source code is available online. Includes an introduction to programming in R. This book is mostly self-contained; the only prerequisites are basic knowledge of probability up to the law of large numbers. Careful presentation and examples make this book accessible to a wide range of students and suitable for self-study or as the basis of a taught course
Provides an introduction to the various statistical techniques involved in medical research and drug development with a focus on estimating the success probability of an experiment Success Probability Estimation with Applications to Clinical Trials details the use of success probability estimation in both the planning and analyzing of clinical trials and in widely used statistical tests. Devoted to both statisticians and non-statisticians who are involved in clinical trials, Part I of the book presents new concepts related to success probability estimation and their usefulness in clinical trials, and each section begins with a non-technical explanation of the presented concepts. Part II delves deeper into the techniques for success probability estimation and features applications to both reproducibility probability estimation and conservative sample size estimation. Success Probability Estimation with Applications to Clinical Trials: • Addresses the theoretical and practical aspects of the topic and introduces new and promising techniques in the statistical and pharmaceutical industries Features practical solutions for problems that are often encountered in clinical trials Includes success probability estimation for widely used statistical tests, such as parametric and nonparametric models Focuses on experimental planning, specifically the sample size of clinical trials using phase II results and data for planning phase III trials Introduces statistical concepts related to success probability estimation and their usefulness in clinical trials Success Probability Estimation with Applications to Clinical Trials is an ideal reference for statisticians and biostatisticians in the pharmaceutical industry as well as researchers and practitioners in medical centers who are actively involved in health policy, clinical research, and the design and evaluation of clinical trials.
This outstanding overview sets a new standard for a methods book on pathogen detection. The first chapter provides an outline of currently used routine methods, including their background, strengths and weaknesses, as well as comparing them to newer methods. The following chapters then cover novel methods already in wide use and which are still more experimental for routine purposes. An invaluable resource for all medical laboratories and clinical institutions dealing with infectious diseases.
This book explores the state-of-the art in computational modelling techniques for photonic devices In this book, the author provides a comprehensive coverage of modern numerical modelling techniques for designing photonic devices for use in modern optical telecommunications systems. In addition the book presents the state-of-the-art in computational photonics techniques, covering methods such as full-vectorial finite-element beam propagation, bidirectional beam propagation, complex-envelope alternative direction implicit finite difference time domain, multiresolution time domain, and finite volume time domain. The book guides the reader through the concepts of modelling, analysing, designing and optimising the performance of a wide range of photonic devices by building their own numerical code using these methods. Key Features: Provides a thorough presentation of the state-of-the art in computational modelling techniques for photonics Contains broad coverage of both frequency- and time-domain techniques to suit a wide range of photonic devices Reviews existing commercial software packages for photonics Presents the advantages and disadvantages of the different modelling techniques as well as their suitability for various photonic devices Shows the reader how to model, analyse, design and optimise the performance of a wide range of photonic devices by building their own numerical code using these methods Accompanying website contains the numerical examples representing the numerical techniques in this book, as well as several design examples (http://www.wiley.com/go/obayya_computational) This book will serve as an invaluable reference for researchers, optical telecommunications engineers, engineers in the photonics industry. PhD and MSc students undertaking courses in the areas of photonics and optical telecommunications will also find this book of interest.
Li Chun Drug Delivery Applications of Noninvasive Imaging. Validation from Biodistribution to Sites of Action
Cost-effective strategies for designing novel drug delivery systems that target a broad range of disease conditions In vivo imaging has become an important tool for the development of new drug delivery systems, shedding new light on the pharmacokinetics, biodistribution, bioavailability, local concentration, and clearance of drug substances for the treatment of human disease, most notably cancer. Written by a team of international experts, this book examines the use of quantitative imaging techniques in designing and evaluating novel drug delivery systems and applications. Drug Delivery Applications of Noninvasive Imaging offers a full arsenal of tested and proven methods, practices and guidance, enabling readers to overcome the many challenges in creating successful new drug delivery systems. The book begins with an introduction to molecular imaging. Next, it covers: In vivo imaging techniques and quantitative analysis Imaging drugs and drug carriers at the site of action, including low-molecular weight radiopharmaceuticals, peptides and proteins, siRNA, cells, and nanoparticles Applications of imaging techniques in administration routes other than intravenous injection, such as pulmonary and oral delivery Translational research leading to clinical applications Imaging drug delivery in large animal models Clinical applications of imaging techniques to guide drug development and drug delivery Chapters are based on a thorough review of the current literature as well as the authors' firsthand experience working with imaging techniques for the development of novel drug delivery systems. Presenting state-of-the-technology applications of imaging in preclinical and clinical evaluation of drug delivery systems, Drug Delivery Applications of Noninvasive Imaging offers cost-effective strategies to pharmaceutical researchers and students for developing drug delivery systems that accurately target a broad range of disease conditions.
Helping tech-savvy marketers and data analysts solve real-world business problems with Excel Using data-driven business analytics to understand customers and improve results is a great idea in theory, but in today's busy offices, marketers and analysts need simple, low-cost ways to process and make the most of all that data. This expert book offers the perfect solution. Written by data analysis expert Wayne L. Winston, this practical resource shows you how to tap a simple and cost-effective tool, Microsoft Excel, to solve specific business problems using powerful analytic techniques—and achieve optimum results. Practical exercises in each chapter help you apply and reinforce techniques as you learn. Shows you how to perform sophisticated business analyses using the cost-effective and widely available Microsoft Excel instead of expensive, proprietary analytical tools Reveals how to target and retain profitable customers and avoid high-risk customers Helps you forecast sales and improve response rates for marketing campaigns Explores how to optimize price points for products and services, optimize store layouts, and improve online advertising Covers social media, viral marketing, and how to exploit both effectively Improve your marketing results with Microsoft Excel and the invaluable techniques and ideas in Marketing Analytics: Data-Driven Techniques with Microsoft Excel.
John Lewell Digital Photography for Next to Nothing. Free and Low Cost Hardware and Software to Help You Shoot Like a Pro
Take photos like a pro without breaking the bank by using FREE and nearly FREE software and hardware explained in this book. Get professional looking shots from a low-cost camera Save money by building your own lighting rigs, tripods, monopods and stabilisers for next to nothing Learn how to use older lenses on modern digital cameras, and make your own macro lens, lens hoods, flash diffusers, flash concentrators, decorative Bokeh effect lenses and more Use dozens of FREE and low cost photo applications for processing, viewing, cataloguing, editing, creating HDR, and photo stitching Build powerful photography processing and editing suites with free software and plugins that go head to head with expensive tools like Adobe Photoshop and Lightroom
Alain Abran Software Project Estimation. The Fundamentals for Providing High Quality Information to Decision Makers
This book introduces theoretical concepts to explain the fundamentals of the design and evaluation of software estimation models. It provides software professionals with vital information on the best software management software out there. End-of-chapter exercises Over 100 figures illustrating the concepts presented throughout the book Examples incorporated with industry data
Praise for the Second Edition «This book has never had a competitor. It is the only book that takes a broad approach to sampling . . . any good personal statistics library should include a copy of this book.» —Technometrics «Well-written . . . an excellent book on an important subject. Highly recommended.» —Choice «An ideal reference for scientific researchers and other professionals who use sampling.» —Zentralblatt Math Features new developments in the field combined with all aspects of obtaining, interpreting, and using sample data Sampling provides an up-to-date treatment of both classical and modern sampling design and estimation methods, along with sampling methods for rare, clustered, and hard-to-detect populations. This Third Edition retains the general organization of the two previous editions, but incorporates extensive new material—sections, exercises, and examples—throughout. Inside, readers will find all-new approaches to explain the various techniques in the book; new figures to assist in better visualizing and comprehending underlying concepts such as the different sampling strategies; computing notes for sample selection, calculation of estimates, and simulations; and more. Organized into six sections, the book covers basic sampling, from simple random to unequal probability sampling; the use of auxiliary data with ratio and regression estimation; sufficient data, model, and design in practical sampling; useful designs such as stratified, cluster and systematic, multistage, double and network sampling; detectability methods for elusive populations; spatial sampling; and adaptive sampling designs. Featuring a broad range of topics, Sampling, Third Edition serves as a valuable reference on useful sampling and estimation methods for researchers in various fields of study, including biostatistics, ecology, and the health sciences. The book is also ideal for courses on statistical sampling at the upper-undergraduate and graduate levels.
BEST PRACTICES TO CREATE AND IMPLEMENTHIGHLY EFFECTIVE WEB SURVEYS Exclusively combining design and sampling issues, Handbook of Web Surveys presents a theoretical yet practical approach to creating and conducting web surveys. From the history of web surveys to various modes of data collection to tips for detecting error, this book thoroughly introduces readers to the this cutting-edge technique and offers tips for creating successful web surveys. The authors provide a history of web surveys and go on to explore the advantages and disadvantages of this mode of data collection. Common challenges involving under-coverage, self-selection, and measurement errors are discussed as well as topics including: Sampling designs and estimation procedures Comparing web surveys to face-to-face, telephone, and mail surveys Errors in web surveys Mixed-mode surveys Weighting techniques including post-stratification, generalized regression estimation, and raking ratio estimation Use of propensity scores to correct bias Web panels Real-world examples illustrate the discussed concepts, methods, and techniques, with related data freely available on the book's Website. Handbook of Web Surveys is an essential reference for researchers in the fields of government, business, economics, and the social sciences who utilize technology to gather, analyze, and draw results from data. It is also a suitable supplement for survey methods courses at the upper-undergraduate and graduate levels.
This book serves as a complete and self-contained introduction to the principles of Computational Fluid Dynamic (CFD) analysis. It is deliberately short (at approximately 300 pages) and can be used as a text for the first part of the course of applied CFD followed by a software tutorial. The main objectives of this non-traditional format are: 1) To introduce and explain, using simple examples where possible, the principles and methods of CFD analysis and to demystify the `black box’ of a CFD software tool, and 2) To provide a basic understanding of how CFD problems are set and which factors affect the success and failure of the analysis. Included in the text are the mathematical and physical foundations of CFD, formulation of CFD problems, basic principles of numerical approximation (grids, consistency, convergence, stability, and order of approximation, etc), methods of discretization with focus on finite difference and finite volume techniques, methods of solution of transient and steady state problems, commonly used numerical methods for heat transfer and fluid flows, plus a brief introduction into turbulence modeling.
Cost Management" was written in response to changes in the global business environment. Unbridled access to information and intense competition has meant that cost accounting has become an increasingly important tool for managers and accountants alike. Most textbooks focus on content knowledge and then expect students to 'magically' demonstrate skills such as decision-making and critical thinking. "Cost Management" better prepares students for professional success by bridging the gaps between Knowledge, Skills and Abilities. Many students fail to recognize the assumptions, limitations, behavioral implications and qualitative factors that influence managerial decision-making. The dynamic, new author team focuses on cost accounting methods, techniques and the quality of cost accounting information used for decision-making to deliver a thoroughly modern treatment of cost accounting topics.