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Handbook of Scheduling: Algorithms, Models, and Performance Analysis (Chapman & Hall/CRC Computer and Information Science Series)
by Joseph Y-T. LeungThis handbook provides full coverage of the most recent and advanced topics in scheduling, assembling researchers from all relevant disciplines to facilitate new insights. Presented in six parts, these experts provides introductory material, complete with tutorials and algorithms, then examine classical scheduling problems. Part 3 explores scheduling models that originate in areas such as computer science, operations research. The following section examines scheduling problems that arise in real-time systems. Part 5 discusses stochastic scheduling and queueing networks, and the final section discusses a range of applications in a variety of areas, from airlines to hospitals.
Handbook of Scientific Proposal Writing
by A.Yavuz OrucInvestigators, their home institutions, and funding agencies play significant roles in the development and outcomes of scientific projects. Submitting a proposal to a funding agency is only one dimension of a multivariable and complex funding process, and understanding this is a good first step toward unlocking the puzzle behind why some research p
Handbook of Sharing Confidential Data: Differential Privacy, Secure Multiparty Computation, and Synthetic Data (ISSN)
by Jörg Drechsler, Daniel Kifer, Jerome Reiter and Aleksandra Slavkovi´cStatistical agencies, research organizations, companies, and other data stewards that seek to share data with the public face a challenging dilemma. They need to protect the privacy and confidentiality of data subjects and their attributes while providing data products that are useful for their intended purposes. In an age when information on data subjects is available from a wide range of data sources, as are the computational resources to obtain that information, this challenge is increasingly difficult. The Handbook of Sharing Confidential Data helps data stewards understand how tools from the data confidentiality literature—specifically, synthetic data, formal privacy, and secure computation—can be used to manage trade-offs in disclosure risk and data usefulness.Key features:• Provides overviews of the potential and the limitations of synthetic data, differential privacy, and secure computation• Offers an accessible review of methods for implementing differential privacy, both from methodological and practical perspectives• Presents perspectives from both computer science and statistical science for addressing data confidentiality and privacy• Describes genuine applications of synthetic data, formal privacy, and secure computation to help practitioners implement these approachesThe handbook is accessible to both researchers and practitioners who work with confidential data. It requires familiarity with basic concepts from probability and data analysis.
Handbook of Simulation Optimization
by Michael C. FuThe Handbook of Simulation Optimization presents an overview of the state of the art of simulation optimization, providing a survey of the most well-established approaches for optimizing stochastic simulation models and a sampling of recent research advances in theory and methodology. Leading contributors cover such topics as discrete optimization via simulation, ranking and selection, efficient simulation budget allocation, random search methods, response surface methodology, stochastic gradient estimation, stochastic approximation, sample average approximation, stochastic constraints, variance reduction techniques, model-based stochastic search methods and Markov decision processes. This single volume should serve as a reference for those already in the field and as a means for those new to the field for understanding and applying the main approaches. The intended audience includes researchers, practitioners and graduate students in the business/engineering fields of operations research, management science, operations management and stochastic control, as well as in economics/finance and computer science.
Handbook of Sinc Numerical Methods (Chapman & Hall/CRC Numerical Analysis and Scientific Computing Series)
by null Frank StengerHandbook of Sinc Numerical Methods presents an ideal road map for handling general numeric problems. Reflecting the author’s advances with Sinc since 1995, the text most notably provides a detailed exposition of the Sinc separation of variables method for numerically solving the full range of partial differential equations (PDEs) of interest to scientists and engineers. This new theory, which combines Sinc convolution with the boundary integral equation (IE) approach, makes for exponentially faster convergence to solutions of differential equations. The basis for the approach is the Sinc method of approximating almost every type of operation stemming from calculus via easily computed matrices of very low dimension.The downloadable resources of this handbook contain roughly 450 MATLAB® programs corresponding to exponentially convergent numerical algorithms for solving nearly every computational problem of science and engineering. While the book makes Sinc methods accessible to users wanting to bypass the complete theory, it also offers sufficient theoretical details for readers who do want a full working understanding of this exciting area of numerical analysis.
Handbook of Spatial Epidemiology (Chapman & Hall/CRC Handbooks of Modern Statistical Methods)
by Andrew B. Lawson Sudipto Banerjee Robert P. Haining María Dolores UgarteHandbook of Spatial Epidemiology explains how to model epidemiological problems and improve inference about disease etiology from a geographical perspective. Top epidemiologists, geographers, and statisticians share interdisciplinary viewpoints on analyzing spatial data and space-time variations in disease incidences. These analyses can provide imp
Handbook of Spatial Point-Pattern Analysis in Ecology (Chapman & Hall/CRC Applied Environmental Statistics)
by Thorsten Wiegand Kirk A. MoloneyThis handbook shows how the techniques of point-pattern analysis are useful for tackling ecological problems. Within an ecological framework, it guides readers through a variety of methods for different data types and aids in the interpretation of the results obtained by point-pattern analysis. Along with the techniques, the book provides a comprehensive selection of real-world examples. Most of the examples are analyzed using the authors' software package Programita. The software and a manual are available online.
Handbook of Spatial Statistics (Chapman & Hall/CRC Handbooks of Modern Statistical Methods)
by Alan E. Gelfand Peter J. Diggle Montserrat Fuentes Peter GuttorpAssembling a collection of very prominent researchers in the field, the Handbook of Spatial Statistics presents a comprehensive treatment of both classical and state-of-the-art aspects of this maturing area. It takes a unified, integrated approach to the material, providing cross-references among chapters.The handbook begins with a historical intro
Handbook of Special Functions: Derivatives, Integrals, Series and Other Formulas
by null Yury A. BrychkovBecause of the numerous applications involved in this field, the theory of special functions is under permanent development, especially regarding the requirements for modern computer algebra methods. The Handbook of Special Functions provides in-depth coverage of special functions, which are used to help solve many of the most difficult problems in
A Handbook of Statistical Analyses using R
by null Torsten Hothorn null Brian S. EverittLike the best-selling first two editions, A Handbook of Statistical Analyses using R, Third Edition provides an up-to-date guide to data analysis using the R system for statistical computing. The book explains how to conduct a range of statistical analyses, from simple inference to recursive partitioning to cluster analysis.New to the Third Edition
A Handbook of Statistical Analyses Using S-PLUS
by Brian S. EverittSince the first edition of this book was published, S-PLUS has evolved markedly with new methods of analysis, new graphical procedures, and a convenient graphical user interface (GUI). Today, S-PLUS is the statistical software of choice for many applied researchers in disciplines ranging from finance to medicine. Combining the command line languag
A Handbook of Statistical Analyses using SAS
by null Geoff Der null Brian S. EverittUpdated to reflect SAS 9.2, A Handbook of Statistical Analyses using SAS, Third Edition continues to provide a straightforward description of how to conduct various statistical analyses using SAS. Each chapter shows how to use SAS for a particular type of analysis. The authors cover inference, analysis of variance, regression, generalized linear mo
Handbook of Statistical Analyses Using Stata
by null Brian S. Everitt null Sophia Rabe-HeskethWith each new release of Stata, a comprehensive resource is needed to highlight the improvements as well as discuss the fundamentals of the software. Fulfilling this need, AHandbook of Statistical Analyses Using Stata, Fourth Edition has been fully updated to provide an introduction to Stata version 9. This edition covers many
Handbook of Statistical Bioinformatics (Springer Handbooks of Computational Statistics)
by Henry Horng-Shing Lu Bernhard Schölkopf Martin T. Wells Hongyu ZhaoNow in its second edition, this handbook collects authoritative contributions on modern methods and tools in statistical bioinformatics with a focus on the interface between computational statistics and cutting-edge developments in computational biology. The three parts of the book cover statistical methods for single-cell analysis, network analysis, and systems biology, with contributions by leading experts addressing key topics in probabilistic and statistical modeling and the analysis of massive data sets generated by modern biotechnology. This handbook will serve as a useful reference source for students, researchers and practitioners in statistics, computer science and biological and biomedical research, who are interested in the latest developments in computational statistics as applied to computational biology.
Handbook of Statistical Bioinformatics
by Bernhard Schölkopf Henry Horng-Shing Lu Hongyu ZhaoNumerous fascinating breakthroughs in biotechnology have generated large volumes and diverse types of high throughput data that demand the development of efficient and appropriate tools in computational statistics integrated with biological knowledge and computational algorithms. This volume collects contributed chapters from leading researchers to survey the many active research topics and promote the visibility of this research area. This volume is intended to provide an introductory and reference book for students and researchers who are interested in the recent developments of computational statistics in computational biology.
Handbook of Statistical Distributions with Applications (Statistics: A Series of Textbooks and Monographs)
by K. KrishnamoorthyEasy-to-Use Reference and Software for Statistical Modeling and TestingHandbook of Statistical Distributions with Applications, Second Edition provides quick access to common and specialized probability distributions for modeling practical problems and performing statistical calculations. Along with many new examples and results, this edition inclu
A Handbook of Statistical Graphics Using SAS ODS
by null Geoff Der null Brian EverittEasily Use SAS to Produce Your GraphicsDiagrams, plots, and other types of graphics are indispensable components in nearly all phases of statistical analysis, from the initial assessment of the data to the selection of appropriate statistical models to the diagnosis of the chosen models once they have been fitted to the data. Harnessing the full gr
Handbook of Statistical Methods and Analyses in Sports (Chapman & Hall/CRC Handbooks of Modern Statistical Methods)
by Jim Albert Mark E. Glickman Ruud H. Koning Tim B. SwartzThis handbook will provide both overviews of statistical methods in sports and in-depth treatment of critical problems and challenges confronting statistical research in sports. The material in the handbook will be organized by major sport (baseball, football, hockey, basketball, and soccer) followed by a section on other sports and general statistical design and analysis issues that are common to all sports. This handbook has the potential to become the standard reference for obtaining the necessary background to conduct serious statistical analyses for sports applications and to appreciate scholarly work in this expanding area.
Handbook of Statistical Methods for Case-Control Studies (Chapman & Hall/CRC Handbooks of Modern Statistical Methods)
by Ørnulf Borgan Norman Breslow Nilanjan Chatterjee Mitchell H. Gail Alastair Scott Chris J. WildHandbook of Statistical Methods for Case-Control Studies is written by leading researchers in the field. It provides an in-depth treatment of up-to-date and currently developing statistical methods for the design and analysis of case-control studies, as well as a review of classical principles and methods. The handbook is designed to serve as a reference text for biostatisticians and quantitatively-oriented epidemiologists who are working on the design and analysis of case-control studies or on related statistical methods research. Though not specifically intended as a textbook, it may also be used as a backup reference text for graduate level courses. Book Sections Classical designs and causal inference, measurement error, power, and small-sample inference Designs that use full-cohort information Time-to-event data Genetic epidemiology About the Editors Ørnulf Borgan is Professor of Statistics, University of Oslo. His book with Andersen, Gill and Keiding on counting processes in survival analysis is a world classic. Norman E. Breslow was, at the time of his death, Professor Emeritus in Biostatistics, University of Washington. For decades, his book with Nick Day has been the authoritative text on case-control methodology. Nilanjan Chatterjee is Bloomberg Distinguished Professor, Johns Hopkins University. He leads a broad research program in statistical methods for modern large scale biomedical studies. Mitchell H. Gail is a Senior Investigator at the National Cancer Institute. His research includes modeling absolute risk of disease, intervention trials, and statistical methods for epidemiology. Alastair Scott was, at the time of his death, Professor Emeritus of Statistics, University of Auckland. He was a major contributor to using survey sampling methods for analyzing case-control data. Chris J. Wild is Professor of Statistics, University of Auckland. His research includes nonlinear regression and methods for fitting models to response-selective data.
Handbook of Statistical Methods for Precision Medicine (ISSN)
by Eric Laber Bibhas Chakraborty Moodie, Erica E. M. Tianxi Cai van der Laan, MarkThe statistical study and development of analytic methodology for individualization of treatments is no longer in its infancy. Many methods of study design, estimation, and inference exist, and the tools available to the analyst are ever growing. This handbook introduces the foundations of modern statistical approaches to precision medicine, bridging key ideas to active lines of current research in precision medicine.The contributions in this handbook vary in their level of assumed statistical knowledge; all contributions are accessible to a wide readership of statisticians and computer scientists including graduate students and new researchers in the area. Many contributions, particularly those that are more comprehensive reviews, are suitable for epidemiologists and clinical researchers with some statistical training. The handbook is split into three sections: Study Design for Precision Medicine, Estimation of Optimal Treatment Strategies, and Precision Medicine in High Dimensions.The first focuses on designed experiments, in many instances, building and extending on the notion of sequential multiple assignment randomized trials. Dose finding and simulation-based designs using agent-based modelling are also featured. The second section contains both introductory contributions and more advanced methods, suitable for estimating optimal adaptive treatment strategies from a variety of data sources including non-experimental (observational) studies. The final section turns to estimation in the many-covariate setting, providing approaches suitable to the challenges posed by electronic health records, wearable devices, or any other settings where the number of possible variables (whether confounders, tailoring variables, or other) is high. Together, these three sections bring together some of the foremost leaders in the field of precision medicine, offering new insights and ideas as this field moves towards its third decade.
Handbook of Statistical Methods for Randomized Controlled Trials (Chapman & Hall/CRC Handbooks of Modern Statistical Methods)
by KyungMann Kim Frank Bretz Ying Kuen K. Cheung Lisa V. HampsonStatistical concepts provide scientific framework in experimental studies, including randomized controlled trials. In order to design, monitor, analyze and draw conclusions scientifically from such clinical trials, clinical investigators and statisticians should have a firm grasp of the requisite statistical concepts. The Handbook of Statistical Methods for Randomized Controlled Trials presents these statistical concepts in a logical sequence from beginning to end and can be used as a textbook in a course or as a reference on statistical methods for randomized controlled trials. Part I provides a brief historical background on modern randomized controlled trials and introduces statistical concepts central to planning, monitoring and analysis of randomized controlled trials. Part II describes statistical methods for analysis of different types of outcomes and the associated statistical distributions used in testing the statistical hypotheses regarding the clinical questions. Part III describes some of the most used experimental designs for randomized controlled trials including the sample size estimation necessary in planning. Part IV describe statistical methods used in interim analysis for monitoring of efficacy and safety data. Part V describe important issues in statistical analyses such as multiple testing, subgroup analysis, competing risks and joint models for longitudinal markers and clinical outcomes. Part VI addresses selected miscellaneous topics in design and analysis including multiple assignment randomization trials, analysis of safety outcomes, non-inferiority trials, incorporating historical data, and validation of surrogate outcomes.
Handbook of Statistics for Teaching and Research in Plant and Crop Science
by null Usha PalaniswamyMore than a textbookit’s also a valuable reference book for researchers and crop science professionals!The Handbook of Statistics for Teaching and Research in Plant and Crop Science presents the fundamental concepts of important statistical methods and experimental designs to the students and researchers who need to apply t
Handbook of Statistics in Clinical Oncology
by John Crowley Antje HoeringAddressing the many challenges that have arisen since the publication of its predecessor, this third edition covers the newest developments involved in the design and analysis of cancer clinical trials. Accessible to statisticians in clinical trials as well as oncologists interested in clinical trial methodology, the book presents up-to-date statistical approaches to the design and analysis of oncology clinical trials. New topics in this edition include trial designs for targeted agents, Bayesian trial design, and the inclusion of high-dimensional data and imaging techniques. This edition also contains numerous figures and examples to better explain concepts.
Handbook of Stochastic Analysis and Applications (Statistics: A Series of Textbooks and Monographs)
by D. Kannan V. LakshmikanthamAn introduction to general theories of stochastic processes and modern martingale theory. The volume focuses on consistency, stability and contractivity under geometric invariance in numerical analysis, and discusses problems related to implementation, simulation, variable step size algorithms, and random number generation.
Handbook of Survival Analysis (Chapman & Hall/CRC Handbooks of Modern Statistical Methods)
by John P. Klein Hans C. van Houwelingen Joseph G. Ibrahim Thomas H. ScheikeHandbook of Survival Analysis presents modern techniques and research problems in lifetime data analysis. This area of statistics deals with time-to-event data that is complicated by censoring and the dynamic nature of events occurring in time.With chapters written by leading researchers in the field, the handbook focuses on advances in survival analysis techniques, covering classical and Bayesian approaches. It gives a complete overview of the current status of survival analysis and should inspire further research in the field. Accessible to a wide range of readers, the book provides:An introduction to various areas in survival analysis for graduate students and novicesA reference to modern investigations into survival analysis for more established researchers A text or supplement for a second or advanced course in survival analysisA useful guide to statistical methods for analyzing survival data experiments for practicing statisticians