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Face Detection and Recognition Theory and Practice

Face Detection and Recognition Theory and Practice

Face detection and recognition are the nonintrusive biometrics of choice in many security applications. Examples of their use include border control driver’s license issuance law enforcement investigations and physical access control. Face Detection and Recognition: Theory and Practice elaborates on and explains the theory and practice of face detection and recognition systems currently in vogue. The book begins with an introduction to the state of the art offering a general review of the available methods and an indication of future research using cognitive neurophysiology. The text then:Explores subspace methods for dimensionality reduction in face image processing statistical methods applied to face detection and intelligent face detection methods dominated by the use of artificial neural networksCovers face detection with colour and infrared face images face detection in real time face detection and recognition using set estimation theory face recognition using evolutionary algorithms and face recognition in frequency domainDiscusses methods for the localization of face landmarks helpful in face recognition methods of generating synthetic face images using set estimation theory and databases of face images available for testing and training systemsFeatures pictorial descriptions of every algorithm as well as downloadable source code (in MATLAB®/PYTHON) and hardware implementation strategies with code examplesDemonstrates how frequency domain correlation techniques can be used supplying exhaustive test resultsFace Detection and Recognition: Theory and Practice provides students researchers and practitioners with a single source for cutting-edge information on the major approaches algorithms and technologies used in automated face detection and recognition. | Face Detection and Recognition Theory and Practice

GBP 59.99
1

Mathematics and Music Composition Perception and Performance

Mathematics and Music Composition Perception and Performance

Mathematics and Music: Composition Perception and Performance Second Edition includes many new sections and more consistent expectations of a student’s experience. The new edition of this popular text is more accessible for students with limited musical backgrounds and only high school mathematics is required. The new edition includes more illustrations than the previous one and the added sections deal with the XronoMorph rhythm generator musical composition and analyzing personal performance. The text teaches the basics of reading music explaining how various patterns in music can be described with mathematics providing mathematical explanations for musical scales harmony and rhythm. The book gives students a deeper appreciation showing how music is informed by both its mathematical and aesthetic structures. Highlights of the Second Edition: Now updated for more consistent expectations of students’ backgrounds More accessible for students with limited musical backgrounds Full-color presentation Includes more thorough coverage of spectrograms for analyzing recorded music Provides a basic introduction to reading music Features new coverage of building and evaluating rhythms | Mathematics and Music Composition Perception and Performance

GBP 42.99
1

Embedded and Networking Systems Design Software and Implementation

Embedded and Networking Systems Design Software and Implementation

Embedded and Networking Systems: Design Software and Implementation explores issues related to the design and synthesis of high-performance embedded computer systems and networks. The emphasis is on the fundamental concepts and analytical techniques that are applicable to a range of embedded and networking applications rather than on specific embedded architectures software development or system-level integration. This system point of view guides designers in dealing with the trade-offs to optimize performance power cost and other system-level non-functional requirements. The book brings together contributions by researchers and experts from around the world offering a global view of the latest research and development in embedded and networking systems. Chapters highlight the evolution and trends in the field and supply a fundamental and analytical understanding of some underlying technologies. Topics include the co-design of embedded systems code optimization for a variety of applications power and performance trade-offs benchmarks for evaluating embedded systems and their components and mobile sensor network systems. The book also looks at novel applications such as mobile sensor systems and video networks. A comprehensive review of groundbreaking technology and applications this book is a timely resource for system designers researchers and students interested in the possibilities of embedded and networking systems. It gives readers a better understanding of an emerging technology evolution that is helping drive telecommunications into the next decade. | Embedded and Networking Systems Design Software and Implementation

GBP 77.99
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Image and Video Compression Fundamentals Techniques and Applications

Image and Video Compression Fundamentals Techniques and Applications

Image and video signals require large transmission bandwidth and storage leading to high costs. The data must be compressed without a loss or with a small loss of quality. Thus efficient image and video compression algorithms play a significant role in the storage and transmission of data. Image and Video Compression: Fundamentals Techniques and Applications explains the major techniques for image and video compression and demonstrates their practical implementation using MATLAB® programs. Designed for students researchers and practicing engineers the book presents both basic principles and real practical applications. In an accessible way the book covers basic schemes for image and video compression including lossless techniques and wavelet- and vector quantization-based image compression and digital video compression. The MATLAB programs enable readers to gain hands-on experience with the techniques. The authors provide quality metrics used to evaluate the performance of the compression algorithms. They also introduce the modern technique of compressed sensing which retains the most important part of the signal while it is being sensed. | Image and Video Compression Fundamentals Techniques and Applications

GBP 59.99
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Big Data and Social Science Data Science Methods and Tools for Research and Practice

Big Data and Social Science Data Science Methods and Tools for Research and Practice

Big Data and Social Science: Data Science Methods and Tools for Research and Practice Second Edition shows how to apply data science to real-world problems covering all stages of a data-intensive social science or policy project. Prominent leaders in the social sciences statistics and computer science as well as the field of data science provide a unique perspective on how to apply modern social science research principles and current analytical and computational tools. The text teaches you how to identify and collect appropriate data apply data science methods and tools to the data and recognize and respond to data errors biases and limitations. Features: Takes an accessible hands-on approach to handling new types of data in the social sciences Presents the key data science tools in a non-intimidating way to both social and data scientists while keeping the focus on research questions and purposes Illustrates social science and data science principles through real-world problems Links computer science concepts to practical social science research Promotes good scientific practice Provides freely available workbooks with data code and practical programming exercises through Binder and GitHub New to the Second Edition: Increased use of examples from different areas of social sciences New chapter on dealing with Bias and Fairness in Machine Learning models Expanded chapters focusing on Machine Learning and Text Analysis Revamped hands-on Jupyter notebooks to reinforce concepts covered in each chapter This classroom-tested book fills a major gap in graduate- and professional-level data science and social science education. It can be used to train a new generation of social data scientists to tackle real-world problems and improve the skills and competencies of applied social scientists and public policy practitioners. It empowers you to use the massive and rapidly growing amounts of available data to interpret economic and social activities in a scientific and rigorous manner. | Big Data and Social Science Data Science Methods and Tools for Research and Practice

GBP 52.99
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Extreme Value Modeling and Risk Analysis Methods and Applications

Extreme Value Modeling and Risk Analysis Methods and Applications

Extreme Value Modeling and Risk Analysis: Methods and Applications presents a broad overview of statistical modeling of extreme events along with the most recent methodologies and various applications. The book brings together background material and advanced topics eliminating the need to sort through the massive amount of literature on the subject. After reviewing univariate extreme value analysis and multivariate extremes the book explains univariate extreme value mixture modeling threshold selection in extreme value analysis and threshold modeling of non-stationary extremes. It presents new results for block-maxima of vine copulas develops time series of extremes with applications from climatology describes max-autoregressive and moving maxima models for extremes and discusses spatial extremes and max-stable processes. The book then covers simulation and conditional simulation of max-stable processes; inference methodologies such as composite likelihood Bayesian inference and approximate Bayesian computation; and inferences about extreme quantiles and extreme dependence. It also explores novel applications of extreme value modeling including financial investments insurance and financial risk management weather and climate disasters clinical trials and sports statistics. Risk analyses related to extreme events require the combined expertise of statisticians and domain experts in climatology hydrology finance insurance sports and other fields. This book connects statistical/mathematical research with critical decision and risk assessment/management applications to stimulate more collaboration between these statisticians and specialists. | Extreme Value Modeling and Risk Analysis Methods and Applications

GBP 44.99
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Bioinformatics and Computational Biology Technological Advancements Applications and Opportunities

Bioinformatics and Computational Biology Technological Advancements Applications and Opportunities

Bioinformatics and Computational Biology: Technological Advancements Applications and Opportunities is an invaluable resource for general and applied researchers who analyze biological data that is generated at an unprecedented rate at the global level. After careful evaluation of the requirements for current trends in bioinformatics and computational biology it is anticipated that the book will provide an insightful resource to the academic and scientific community. Through a myriad of computational resources algorithms and methods it equips readers with the confidence to both analyze biological data and estimate predictions. The book offers comprehensive coverage of the most essential and emerging topics: Cloud-based monitoring of bioinformatics multivariate data with cloud platforms Machine learning and deep learning in bioinformatics Quantum machine learning for biological applications Integrating machine learning strategies with multiomics to augment prognosis in chronic diseases Biomedical engineering Next generation sequencing techniques and applications Computational systems biology and molecular evolution While other books may touch on some of the same issues and nuances of biological data analysis they neglect to feature bioinformatics and computational biology exclusively and as exhaustively. This book's abundance of several subtopics related to almost all of the regulatory activities of biomolecules from where real data is being generated brings an added dimension. | Bioinformatics and Computational Biology Technological Advancements Applications and Opportunities

GBP 120.00
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Advanced Wireless Communication and Sensor Networks Applications and Simulations

Advanced Wireless Communication and Sensor Networks Applications and Simulations

This book covers wireless communication security issues advanced wireless sensor networks (WSNs) routing protocols of WSNs with cross-layer solutions emerging trends in the advanced WSNs power management distributed sensing and data gathering techniques for WSNs WSNs security applications research of advanced WSNs with simulation results and simulation tools for WSNs. Features: Covers technologies supporting advanced wireless communication systems sensor networks and the conceptual development of the subject Discusses advanced data gathering and sharing/ distributed sensing techniques with its business applicability Includes numerous worked-out mathematical equations and formulas as well as essential principles including figures illustrations algorithms and flow charts Provides pervasive background knowledge including both wireless communications and WSNs Covers wireless networks as well as sensor network models in detail This book is aimed at graduate students researchers and academics working in the field of computer science wireless communication technology and advanced WSNs. | Advanced Wireless Communication and Sensor Networks Applications and Simulations

GBP 110.00
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Generative Adversarial Networks and Deep Learning Theory and Applications

Generative Adversarial Networks and Deep Learning Theory and Applications

This book explores how to use generative adversarial networks in a variety of applications and emphasises their substantial advancements over traditional generative models. This book's major goal is to concentrate on cutting-edge research in deep learning and generative adversarial networks which includes creating new tools and methods for processing text images and audio. A Generative Adversarial Network (GAN) is a class of machine learning framework and is the next emerging network in deep learning applications. Generative Adversarial Networks(GANs) have the feasibility to build improved models as they can generate the sample data as per application requirements. There are various applications of GAN in science and technology including computer vision security multimedia and advertisements image generation image translation text-to-images synthesis video synthesis generating high-resolution images drug discovery etc. Features: Presents a comprehensive guide on how to use GAN for images and videos. Includes case studies of Underwater Image Enhancement Using Generative Adversarial Network Intrusion detection using GAN Highlights the inclusion of gaming effects using deep learning methods Examines the significant technological advancements in GAN and its real-world application. Discusses as GAN challenges and optimal solutions The book addresses scientific aspects for a wider audience such as junior and senior engineering undergraduate and postgraduate students researchers and anyone interested in the trends development and opportunities in GAN and Deep Learning. The material in the book can serve as a reference in libraries accreditation agencies government agencies and especially the academic institution of higher education intending to launch or reform their engineering curriculum | Generative Adversarial Networks and Deep Learning Theory and Applications

GBP 140.00
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Introduction to Modeling and Simulation with MATLAB and Python

Introduction to Modeling and Simulation with MATLAB and Python

Introduction to Modeling and Simulation with MATLAB and Python is intended for students and professionals in science social science and engineering that wish to learn the principles of computer modeling as well as basic programming skills. The book content focuses on meeting a set of basic modeling and simulation competencies that were developed as part of several National Science Foundation grants. Even though computer science students are much more expert programmers they are not often given the opportunity to see how those skills are being applied to solve complex science and engineering problems and may also not be aware of the libraries used by scientists to create those models. The book interleaves chapters on modeling concepts and related exercises with programming concepts and exercises. The authors start with an introduction to modeling and its importance to current practices in the sciences and engineering. They introduce each of the programming environments and the syntax used to represent variables and compute mathematical equations and functions. As students gain more programming expertise the authors return to modeling concepts providing starting code for a variety of exercises where students add additional code to solve the problem and provide an analysis of the outcomes. In this way the book builds both modeling and programming expertise with a just-in-time approach so that by the end of the book students can take on relatively simple modeling example on their own. Each chapter is supplemented with references to additional reading tutorials and exercises that guide students to additional help and allows them to practice both their programming and analytical modeling skills. In addition each of the programming related chapters is divided into two parts – one for MATLAB and one for Python. In these chapters the authors also refer to additional online tutorials that students can use if they are having difficulty with any of the topics. The book culminates with a set of final project exercise suggestions that incorporate both the modeling and programming skills provided in the rest of the volume. Those projects could be undertaken by individuals or small groups of students. The companion website at http://www. intromodeling. com provides updates to instructions when there are substantial changes in software versions as well as electronic copies of exercises and the related code. The website also offers a space where people can suggest additional projects they are willing to share as well as comments on the existing projects and exercises throughout the book. Solutions and lecture notes will also be available for qualifying instructors. | Introduction to Modeling and Simulation with MATLAB® and Python

GBP 44.99
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Deep and Shallow Machine Learning in Music and Audio

Deep and Shallow Machine Learning in Music and Audio

Providing an essential and unique bridge between the theories of signal processing machine learning and artificial intelligence (AI) in music this book provides a holistic overview of foundational ideas in music from the physical and mathematical properties of sound to symbolic representations. Combining signals and language models in one place this book explores how sound may be represented and manipulated by computer systems and how our devices may come to recognize particular sonic patterns as musically meaningful or creative through the lens of information theory. Introducing popular fundamental ideas in AI at a comfortable pace more complex discussions around implementations and implications in musical creativity are gradually incorporated as the book progresses. Each chapter is accompanied by guided programming activities designed to familiarize readers with practical implications of discussed theory without the frustrations of free-form coding. Surveying state-of-the art methods in applications of deep neural networks to audio and sound computing as well as offering a research perspective that suggests future challenges in music and AI research this book appeals to both students of AI and music as well as industry professionals in the fields of machine learning music and AI. | Deep and Shallow Machine Learning in Music and Audio

GBP 44.99
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Equivalence and Noninferiority Tests for Quality Manufacturing and Test Engineers

Equivalence and Noninferiority Tests for Quality Manufacturing and Test Engineers

In engineering and quality control various situations including process validation and design verification require equivalence and noninferiority tests. Equivalence and Noninferiority Tests for Quality Manufacturing and Test Engineers presents methods for using validation and verification test data to demonstrate equivalence and noninferiority in engineering and applied science. The book covers numerous tests drawn from the author’s more than 30 years of work in a range of industrial settings. It provides computational formulas for the tests methods to determine or justify sample sizes and formulas to calculate power and operating characteristic curves. The methods are accessible using standard statistical software and do not require complicated programming. The book also includes computer code and screen shots for SAS R and JMP. This book provides you with a guide to performing validation and verification tests that demonstrate the adequacy of your process system or product. It will help you choose the best test for your application.

GBP 59.99
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Spatiotemporal Patterns in Ecology and Epidemiology Theory Models and Simulation

Spatiotemporal Patterns in Ecology and Epidemiology Theory Models and Simulation

Although the spatial dimension of ecosystem dynamics is now widely recognized the specific mechanisms behind species patterning in space are still poorly understood and the corresponding theoretical framework is underdeveloped. Going beyond the classical Turing scenario of pattern formation Spatiotemporal Patterns in Ecology and Epidemiology: Theory Models and Simulation illustrates how mathematical modeling and numerical simulations can lead to greater understanding of these issues. It takes a unified approach to population dynamics and epidemiology by presenting several ecoepidemiological models where both the basic interspecies interactions of population dynamics and the impact of an infectious disease are explicitly considered. The book first describes relevant phenomena in ecology and epidemiology provides examples of pattern formation in natural systems and summarizes existing modeling approaches. The authors then explore nonspatial models of population dynamics and epidemiology. They present the main scenarios of spatial and spatiotemporal pattern formation in deterministic models of population dynamics. The book also addresses the interaction between deterministic and stochastic processes in ecosystem and epidemic dynamics discusses the corresponding modeling approaches and examines how noise and stochasticity affect pattern formation. Reviewing the significant progress made in understanding spatiotemporal patterning in ecological and epidemiological systems this resource shows that mathematical modeling and numerical simulations are effective tools in the study of population ecology and epidemiology. | Spatiotemporal Patterns in Ecology and Epidemiology Theory Models and Simulation

GBP 59.99
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Design and Analysis of Experiments and Observational Studies using R

Design and Analysis of Experiments and Observational Studies using R

Introduction to Design and Analysis of Scientific Studies exposes undergraduate and graduate students to the foundations of classical experimental design and observational studies through a modern framework - The Rubin Causal Model. A causal inference framework is important in design data collection and analysis since it provides a framework for investigators to readily evaluate study limitations and draw appropriate conclusions. R is used to implement designs and analyse the data collected. Features: Classical experimental design with an emphasis on computation using tidyverse packages in R. Applications of experimental design to clinical trials A/B testing and other modern examples. Discussion of the link between classical experimental design and causal inference. The role of randomization in experimental design and sampling in the big data era. Exercises with solutions. Instructor slides in RMarkdown a new R package will be developed to be used with book and a bookdown version of the book will be freely available. The proposed book will emphasize ethics communication and decision making as part of design data analysis and statistical thinking. | Design and Analysis of Experiments and Observational Studies using R

GBP 82.99
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Discrete and Continuous Fourier Transforms Analysis Applications and Fast Algorithms

Discrete and Continuous Fourier Transforms Analysis Applications and Fast Algorithms

Long employed in electrical engineering the discrete Fourier transform (DFT) is now applied in a range of fields through the use of digital computers and fast Fourier transform (FFT) algorithms. But to correctly interpret DFT results it is essential to understand the core and tools of Fourier analysis. Discrete and Continuous Fourier Transforms: Analysis Applications and Fast Algorithms presents the fundamentals of Fourier analysis and their deployment in signal processing using DFT and FFT algorithms. This accessible self-contained book provides meaningful interpretations of essential formulas in the context of applications building a solid foundation for the application of Fourier analysis in the many diverging and continuously evolving areas in digital signal processing enterprises. It comprehensively covers the DFT of windowed sequences various discrete convolution algorithms and their applications in digital filtering and filters and many FFT algorithms unified under the frameworks of mixed-radix FFTs and prime factor FFTs. A large number of graphical illustrations and worked examples help explain the concepts and relationships from the very beginning of the text. Requiring no prior knowledge of Fourier analysis or signal processing this book supplies the basis for using FFT algorithms to compute the DFT in a variety of application areas. | Discrete and Continuous Fourier Transforms Analysis Applications and Fast Algorithms

GBP 56.99
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Sound and Robotics Speech Non-Verbal Audio and Robotic Musicianship

Sound and Robotics Speech Non-Verbal Audio and Robotic Musicianship

Sound in human–robot interaction currently encompasses a wide range of approaches and methodologies not easily classified analyzed or compared among projects. This edited book covers the state of the art in sound and robotics aiming to gather existing approaches in a combined volume. Collecting chapters from world-leading academic and industry authors Sound and Robotics: Speech Non-Verbal Audio and Robotic Musicianship explores how robots can communicate through speech non-verbal audio and music. The first set of chapters explores how robots use verbal communication considering the possibilities of speech for human–robot interaction. The second section shifts to roles of non-verbal communication in HRI including consequential sound sonification and audio cues. The third and final section describes current approaches to robotic musicianship and their evaluation. This book is primarily aimed at HRI researchers ranging from those who have never used sound to those very experienced with sound. Alongside robotic researchers this book will present avenues for a diverse range of musicians composers and sound designers to become introduced to the world of HRI and learn of potential creative directions in robotics. | Sound and Robotics Speech Non-Verbal Audio and Robotic Musicianship

GBP 44.99
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Geospatial Health Data Modeling and Visualization with R-INLA and Shiny

Geospatial Health Data Modeling and Visualization with R-INLA and Shiny

Geospatial health data are essential to inform public health and policy. These data can be used to quantify disease burden understand geographic and temporal patterns identify risk factors and measure inequalities. Geospatial Health Data: Modeling and Visualization with R-INLA and Shiny describes spatial and spatio-temporal statistical methods and visualization techniques to analyze georeferenced health data in R. The book covers the following topics: Manipulating and transforming point areal and raster data Bayesian hierarchical models for disease mapping using areal and geostatistical data Fitting and interpreting spatial and spatio-temporal models with the integrated nested Laplace approximation (INLA) and the stochastic partial differential equation (SPDE) approaches Creating interactive and static visualizations such as disease maps and time plots Reproducible R Markdown reports interactive dashboards and Shiny web applications that facilitate the communication of insights to collaborators and policymakers. The book features fully reproducible examples of several disease and environmental applications using real-world data such as malaria in The Gambia cancer in Scotland and USA and air pollution in Spain. Examples in the book focus on health applications but the approaches covered are also applicable to other fields that use georeferenced data including epidemiology ecology demography or criminology. The book provides clear descriptions of the R code for data importing manipulation modelling and visualization as well as the interpretation of the results. This ensures contents are fully reproducible and accessible for students researchers and practitioners. | Geospatial Health Data Modeling and Visualization with R-INLA and Shiny

GBP 84.99
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Statistical Design Monitoring and Analysis of Clinical Trials Principles and Methods

Statistical Design Monitoring and Analysis of Clinical Trials Principles and Methods

Statistical Design Monitoring and Analysis of Clinical Trials Second Edition concentrates on the biostatistics component of clinical trials. This new edition is updated throughout and includes five new chapters. Developed from the authors’ courses taught to public health and medical students residents and fellows during the past 20 years the text shows how biostatistics in clinical trials is an integration of many fundamental scientific principles and statistical methods. The book begins with ethical and safety principles core trial design concepts the principles and methods of sample size and power calculation and analysis of covariance and stratified analysis. It then focuses on sequential designs and methods for two-stage Phase II cancer trials to Phase III group sequential trials covering monitoring safety futility and efficacy. The authors also discuss the development of sample size reestimation and adaptive group sequential procedures phase 2/3 seamless design and trials with predictive biomarkers exploit multiple testing procedures and explain the concept of estimand intercurrent events and different missing data processes and describe how to analyze incomplete data by proper multiple imputations. This text reflects the academic research commercial development and public health aspects of clinical trials. It gives students and practitioners a multidisciplinary understanding of the concepts and techniques involved in designing monitoring and analyzing various types of trials. The book’s balanced set of homework assignments and in-class exercises are appropriate for students and researchers in (bio)statistics epidemiology medicine pharmacy and public health. | Statistical Design Monitoring and Analysis of Clinical Trials Principles and Methods

GBP 82.99
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Basic Experimental Strategies and Data Analysis for Science and Engineering

Basic Experimental Strategies and Data Analysis for Science and Engineering

Every technical investigation involving trial-and-error experimentation embodies a strategy for deciding what experiments to perform when to quit and how to interpret the data. This handbook presents several statistically derived strategies which are more efficient than any intuitive approach and will get the investigator to their goal with the fewest experiments give the greatest degree of reliability to their conclusions and keep the risk of overlooking something of practical importance to a minimum. Features:Provides a comprehensive desk reference on experimental design that will be useful to practitioners without extensive statistical knowledgeFeatures a review of the necessary statistical prerequisitesPresents a set of tables that allow readers to quickly access various experimental designsIncludes a roadmap for where and when to use various experimental design strategiesShows compelling examples of each method discussedIllustrates how to reproduce results using several popular software packages on a supplementary websiteFollowing the outlines and examples in this book should quickly allow a working professional or student to select the appropriate experimental design for a research problem at hand follow the design to conduct the experiments and analyze and interpret the resulting data. John Lawson and John Erjavec have a combined 25 years of industrial experience and over 40 years of academic experience. They have taught this material to numerous practicing engineers and scientists as well as undergraduate and graduate students. | Basic Experimental Strategies and Data Analysis for Science and Engineering

GBP 44.99
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Applications of Optimization and Machine Learning in Image Processing and IoT

Applications of Optimization and Machine Learning in Image Processing and IoT

This book presents state-of-the-art optimization algorithms followed by Internet of Things (IoT) fundamentals. The applications of machine learning and IoT are explored with topics including optimization algorithms and machine learning in image processing and IoT. Applications of Optimization and Machine Learning in Image Processing and IoT is a complete reference source providing the latest research findings and solutions for optimization and machine learning algorithms. The chapters examine and discuss the fields of machine learning IoT and image processing. KEY FEATURES: • Includes fundamental concepts towards advanced applications in machine learning and IoT. • Discusses potential and challenges of machine learning for IoT and optimization • Reviews recent advancements in diverse researches on computer vision networking and optimization field. • Presents latest technologies such as machine learning in image processing and IoT This book has been written for readers in academia engineering IT specialists researchers industrial professionals and students and is a great reference for those just starting out in the field as well as those at an advanced level.

GBP 48.99
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Meta-analysis and Combining Information in Genetics and Genomics

Meta-analysis and Combining Information in Genetics and Genomics

Novel Techniques for Analyzing and Combining Data from Modern Biological StudiesBroadens the Traditional Definition of Meta-Analysis With the diversity of data and meta-data now available there is increased interest in analyzing multiple studies beyond statistical approaches of formal meta-analysis. Covering an extensive range of quantitative information combination methods Meta-analysis and Combining Information in Genetics and Genomics looks at how to analyze multiple studies from a broad perspective. After presenting the basic ideas and tools of meta-analysis the book addresses the combination of similar data types: genotype data from genome-wide linkage scans and data derived from microarray gene expression experiments. The expert contributors show how some data combination problems can arise even within the same basic framework and offer solutions to these problems. They also discuss the combined analysis of different data types giving readers an opportunity to see data combination approaches in action across a wide variety of genome-scale investigations. As heterogeneous data sets become more common biological understanding will be significantly aided by jointly analyzing such data using fundamentally sound statistical methodology. This book provides many novel techniques for analyzing data from modern biological studies that involve multiple data sets either of the same type or multiple data sources.

GBP 69.99
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Absolute Risk Methods and Applications in Clinical Management and Public Health

Absolute Risk Methods and Applications in Clinical Management and Public Health

Absolute Risk: Methods and Applications in Clinical Management and Public Health provides theory and examples to demonstrate the importance of absolute risk in counseling patients devising public health strategies and clinical management. The book provides sufficient technical detail to allow statisticians epidemiologists and clinicians to build test and apply models of absolute risk. Features:Provides theoretical basis for modeling absolute risk including competing risks and cause-specific and cumulative incidence regression Discusses various sampling designs for estimating absolute risk and criteria to evaluate modelsProvides details on statistical inference for the various sampling designsDiscusses criteria for evaluating risk models and comparing risk models including both general criteria and problem-specific expected losses in well-defined clinical and public health applications Describes many applications encompassing both disease prevention and prognosis and ranging from counseling individual patients to clinical decision making to assessing the impact of risk-based public health strategies Discusses model updating family-based designs dynamic projections and other topicsRuth M. Pfeiffer is a mathematical statistician and Fellow of the American Statistical Association with interests in risk modeling dimension reduction and applications in epidemiology. She developed absolute risk models for breast cancer colon cancer melanoma and second primary thyroid cancer following a childhood cancer diagnosis. Mitchell H. Gail developed the widely used Gail model for projecting the absolute risk of invasive breast cancer. He is a medical statistician with interests in statistical methods and applications in epidemiology and molecular medicine. He is a member of the National Academy of Medicine and former President of the American Statistical Association. Both are Senior Investigators in the Division of Cancer Epidemiology and Genetics National Cancer Institute National Institutes of Health. | Absolute Risk Methods and Applications in Clinical Management and Public Health

GBP 46.99
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Design and Analysis of Experiments Classical and Regression Approaches with SAS

Design and Analysis of Experiments Classical and Regression Approaches with SAS

Unlike other books on the modeling and analysis of experimental data Design and Analysis of Experiments: Classical and Regression Approaches with SAS not only covers classical experimental design theory it also explores regression approaches. Capitalizing on the availability of cutting-edge software the author uses both manual methods and SAS programs to carry out analyses. The book presents most of the different designs covered in a typical experimental design course. It discusses the requirements for good experimentation the completely randomized design the use of orthogonal contrast to test hypotheses and the model adequacy check. With an emphasis on two-factor factorial experiments the author analyzes repeated measures as well as fixed random and mixed effects models. He also describes designs with randomization restrictions before delving into the special cases of the 2k and 3k factorial designs including fractional replication and confounding. In addition the book covers response surfaces balanced incomplete block and hierarchical designs ANOVA ANCOVA and MANOVA. Fortifying the theory and computations with practical exercises and supplemental material this distinctive text provides a modern comprehensive treatment of experimental design and analysis. | Design and Analysis of Experiments Classical and Regression Approaches with SAS

GBP 59.99
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Using R and RStudio for Data Management Statistical Analysis and Graphics

Using R and RStudio for Data Management Statistical Analysis and Graphics

Improve Your Analytical SkillsIncorporating the latest R packages as well as new case studies and applications Using R and RStudio for Data Management Statistical Analysis and Graphics Second Edition covers the aspects of R most often used by statistical analysts. New users of R will find the book’s simple approach easy to understand while more sophisticated users will appreciate the invaluable source of task-oriented information. New to the Second EditionThe use of RStudio which increases the productivity of R users and helps users avoid error-prone cut-and-paste workflowsNew chapter of case studies illustrating examples of useful data management tasks reading complex files making and annotating maps scraping data from the web mining text files and generating dynamic graphicsNew chapter on special topics that describes key features such as processing by group and explores important areas of statistics including Bayesian methods propensity scores and bootstrappingNew chapter on simulation that includes examples of data generated from complex models and distributions A detailed discussion of the philosophy and use of the knitr and markdown packages for RNew packages that extend the functionality of R and facilitate sophisticated analysesReorganized and enhanced chapters on data input and output data management statistical and mathematical functions programming high-level graphics plots and the customization of plotsEasily Find Your Desired TaskConveniently organized by short clear descriptive entries this edition continues to show users how to easily perform an analytical task in R. Users can quickly find and implement the material they need through the extensive indexing cross-referencing and worked examples in the text. Datasets and code are available for download on a supplementary website.

GBP 44.99
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