Pricemate

Multi-State Survival Models for Interval-Censored Data

Multi-State Survival Models for Interval-Censored Data introduces methods to describe stochastic processes that consist of transitions between states over time. It is targeted at researchers in medical statistics epidemiology demography and social statistics. One of the applications in the book is a three-state process for dementia and survival in the older population. This process is described by an illness-death model with a dementia-free state a dementia state and a dead state. Statistical modelling of a multi-state process can investigate potential associations between the risk of moving to the next state and variables such as age gender or education. A model can also be used to predict the multi-state process. The methods are for longitudinal data subject to interval censoring. Depending on the definition of a state it is possible that the time of the transition into a state is not observed exactly. However when longitudinal data are available the transition time may be known to lie in the time interval defined by two successive observations. Such an interval-censored observation scheme can be taken into account in the statistical inference. Multi-state modelling is an elegant combination of statistical inference and the theory of stochastic processes. Multi-State Survival Models for Interval-Censored Data shows that the statistical modelling is versatile and allows for a wide range of applications.

GBP 48.99

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Pocket Book of Integrals and Mathematical Formulas

Pocket Book of Integrals and Mathematical Formulas 5th Edition covers topics ranging from precalculus to vector analysis and from Fourier series to statistics presenting numerous worked examples to demonstrate the application of the formulas and methods. This popular pocket book is an essential source for students of calculus and higher mathematics courses. It also provides an easy-to-use accessible reference for mathematicians engineers scientists and others seeking vital mathematical formulas concepts and definitions. Enlarging the type without sacrificing special topics involving financial mathematics and number theory this 5th Edition: Includes several classic calculus applications that illustrate the power and practical use of calculus Discusses an interesting offshoot of Fermat‘s last theorem namely near misses Reformats and revises the table of integrals for improved clarity and accuracy Through careful selection of topics and detail Pocket Book of Integrals and Mathematical Formulas 5th Edition remains a portable yet comprehensive resource for students and professionals containing the most important mathematical formulas for engineering and scientific applications.

GBP 170.00

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Programming for Hybrid Multi/Manycore MPP Systems

Ask not what your compiler can do for you ask what you can do for your compiler. John Levesque Director of Cray’s Supercomputing Centers of ExcellenceThe next decade of computationally intense computing lies with more powerful multi/manycore nodes where processors share a large memory space. These nodes will be the building block for systems that range from a single node workstation up to systems approaching the exaflop regime. The node itself will consist of 10’s to 100’s of MIMD (multiple instruction multiple data) processing units with SIMD (single instruction multiple data) parallel instructions. Since a standard affordable memory architecture will not be able to supply the bandwidth required by these cores new memory organizations will be introduced. These new node architectures will represent a significant challenge to application developers. Programming for Hybrid Multi/Manycore MPP Systems attempts to briefly describe the current state-of-the-art in programming these systems and proposes an approach for developing a performance-portable application that can effectively utilize all of these systems from a single application. The book starts with a strategy for optimizing an application for multi/manycore architectures. It then looks at the three typical architectures covering their advantages and disadvantages. The next section of the book explores the other important component of the target—the compiler. The compiler will ultimately convert the input language to executable code on the target and the book explores how to make the compiler do what we want. The book then talks about gathering runtime statistics from running the application on the important problem sets previously discussed. How best to utilize available memory bandwidth and virtualization is covered next along with hybridization of a program. The last part of the book includes several major applications and examines future hardware advancements and how the application developer may prepare for those advancements.

GBP 44.99

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Advanced Studies in Multi-Criteria Decision Making

With contributions from some of the top academics and scientists in the field Advanced Studies in Multi-Criteria Decision Making presents an updated view of the landscape of Decision Sciences current research topics the interaction with other sciences and fields as well as the prospects and challenges at an international level. Given that Decision Sciences are recognized today as indispensable for confronting the major societal challenges in science and technology this book would be of interest to decision-makers managers and researchers from academia and industrial/services companies that would like a fresh insight into MCDM. FeaturesIntegrates a wide range of scientific fields with a general reader approach including applied researchers from the social business enterprise sciencesSuitable for academics and professionalsPresents a broad coverage of MCDM tools either in industry or in services companies and systemsProvides a fresh overview on MCDM studies promoted by prestigious R&D institutions

GBP 44.99

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Quantitative Trading Algorithms Analytics Data Models Optimization

The first part of this book discusses institutions and mechanisms of algorithmic trading market microstructure high-frequency data and stylized facts time and event aggregation order book dynamics trading strategies and algorithms transaction costs market impact and execution strategies risk analysis and management. The second part covers market impact models network models multi-asset trading machine learning techniques and nonlinear filtering. The third part discusses electronic market making liquidity systemic risk recent developments and debates on the subject. | Quantitative Trading Algorithms Analytics Data Models Optimization

GBP 56.99

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Mathematics of Keno and Lotteries

Mathematics of Keno and Lotteries is an elementary treatment of the mathematics primarily probability and simple combinatorics involved in lotteries and keno. Keno has a long history as a high-advantage high-payoff casino game and state lottery games such as Powerball are mathematically similar. MKL also considers such lottery games as passive tickets daily number drawings and specialized games offered around the world. In addition there is a section on financial mathematics that explains the connection between lump-sum lottery prizes (as with Powerball) and their multi-year annuity options. So-called winning systems for keno and lotteries are examined mathematically and their flaws identified.

GBP 52.99

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Evaluating Climate Change Impacts

Evaluating Climate Change Impacts discusses assessing and quantifying climate change and its impacts from a multi-faceted perspective of ecosystem social and infrastructure resilience given through a lens of statistics and data science. It provides a multi-disciplinary view on the implications of climate variability and shows how the new data science paradigm can help us to mitigate climate-induced risk and to enhance climate adaptation strategies. This book consists of chapters solicited from leading topical experts and presents their perspectives on climate change effects in two general areas: natural ecosystems and socio-economic impacts. The chapters unveil topics of atmospheric circulation climate modeling and long-term prediction; approach the problems of increasing frequency of extreme events sea level rise and forest fires as well as economic losses analysis of climate impacts for insurance agriculture fisheries and electric and transport infrastructures. The reader will be exposed to the current research using a variety of methods from physical modeling statistics and machine learning including the global circulation models (GCM) and ocean models statistical generalized additive models (GAM) and generalized linear models (GLM) state space and graphical models causality networks Bayesian ensembles a variety of index methods and statistical tests and machine learning methods. The reader will learn about data from various sources including GCM and ocean model outputs satellite observations and data collected by different agencies and research units. Many of the chapters provide references to open source software R and Python code that are available for implementing the methods.

GBP 54.99

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Parallel Programming for Modern High Performance Computing Systems

In view of the growing presence and popularity of multicore and manycore processors accelerators and coprocessors as well as clusters using such computing devices the development of efficient parallel applications has become a key challenge to be able to exploit the performance of such systems. This book covers the scope of parallel programming for modern high performance computing systems. It first discusses selected and popular state-of-the-art computing devices and systems available today These include multicore CPUs manycore (co)processors such as Intel Xeon Phi accelerators such as GPUs and clusters as well as programming models supported on these platforms. It next introduces parallelization through important programming paradigms such as master-slave geometric Single Program Multiple Data (SPMD) and divide-and-conquer. The practical and useful elements of the most popular and important APIs for programming parallel HPC systems are discussed including MPI OpenMP Pthreads CUDA OpenCL and OpenACC. It also demonstrates through selected code listings how selected APIs can be used to implement important programming paradigms. Furthermore it shows how the codes can be compiled and executed in a Linux environment. The book also presents hybrid codes that integrate selected APIs for potentially multi-level parallelization and utilization of heterogeneous resources and it shows how to use modern elements of these APIs. Selected optimization techniques are also included such as overlapping communication and computations implemented using various APIs. Features:Discusses the popular and currently available computing devices and cluster systemsIncludes typical paradigms used in parallel programsExplores popular APIs for programming parallel applicationsProvides code templates that can be used for implementation of paradigmsProvides hybrid code examples allowing multi-level parallelizationCovers the optimization of parallel programs

GBP 44.99

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Handbook of Approximation Algorithms and Metaheuristics Methologies and Traditional Applications Volume 1

Handbook of Approximation Algorithms and Metaheuristics Second Edition reflects the tremendous growth in the field over the past two decades. Through contributions from leading experts this handbook provides a comprehensive introduction to the underlying theory and methodologies as well as the various applications of approximation algorithms and metaheuristics. Volume 1 of this two-volume set deals primarily with methodologies and traditional applications. It includes restriction relaxation local ratio approximation schemes randomization tabu search evolutionary computation local search neural networks and other metaheuristics. It also explores multi-objective optimization reoptimization sensitivity analysis and stability. Traditional applications covered include: bin packing multi-dimensional packing Steiner trees traveling salesperson scheduling and related problems. Volume 2 focuses on the contemporary and emerging applications of methodologies to problems in combinatorial optimization computational geometry and graphs problems as well as in large-scale and emerging application areas. It includes approximation algorithms and heuristics for clustering networks (sensor and wireless) communication bioinformatics search streams virtual communities and more. About the EditorTeofilo F. Gonzalez is a professor emeritus of computer science at the University of California Santa Barbara. He completed his Ph. D. in 1975 from the University of Minnesota. He taught at the University of Oklahoma the Pennsylvania State University and the University of Texas at Dallas before joining the UCSB computer science faculty in 1984. He spent sabbatical leaves at the Monterrey Institute of Technology and Higher Education and Utrecht University. He is known for his highly cited pioneering research in the hardness of approximation; for his sublinear and best possible approximation algorithm for k-tMM clustering; for introducing the open-shop scheduling problem as well as algorithms for its solution that have found applications in numerous research areas; as well as for his research on problems in the areas of job scheduling graph algorithms computational geometry message communication wire routing etc. | Handbook of Approximation Algorithms and Metaheuristics Methologies and Traditional Applications Volume 1

GBP 44.99

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Correspondence Analysis in Practice

Drawing on the author’s 45 years of experience in multivariate analysis Correspondence Analysis in Practice Third Edition shows how the versatile method of correspondence analysis (CA) can be used for data visualization in a wide variety of situations. CA and its variants subset CA multiple CA and joint CA translate two-way and multi-way tables into more readable graphical forms — ideal for applications in the social environmental and health sciences as well as marketing economics linguistics archaeology and more. Michael Greenacre is Professor of Statistics at the Universitat Pompeu Fabra Barcelona Spain where he teaches a course amongst others on Data Visualization. He has authored and co-edited nine books and 80 journal articles and book chapters mostly on correspondence analysis the latest being Visualization and Verbalization of Data in 2015. He has given short courses in fifteen countries to environmental scientists sociologists data scientists and marketing professionals and has specialized in statistics in ecology and social science.

GBP 48.99

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CRC Standard Mathematical Tables and Formulas

Containing more than 6 000 entries CRC Standard Mathematical Tables and Formulas 33rd Edition continues to provide essential formulas tables figures and detailed descriptions. The newest edition of this popular series also features many diagrams group tables and integrals that are not available online. This edition also incorporates important topics such as max plus algebra financial options pseudospectra and proof methods. Newly updated topics reflecting new results include couple analogues radar and significant equations of mathematics. New features of the 33rd edition include: Larger trim size five new topics and topics which have been modified to update results Provides practical ready-to-use information and covers important topics that are unfamiliar to many readers such as visual proofs and sequences Includes hard-to-find and more complete information than found in the Internet such as table of conformal mappings and integral tables Adds descriptions of new functions: Lambert prolate spheroidal and Weierstrass Even though the book has been updated it retains the same successful format of previous editions in that material is still presented in a multi-sectional format.

GBP 94.99

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Machine Learning Animated

The release of ChatGPT has kicked off an arms race in Machine Learning (ML) however ML has also been described as a black box and very hard to understand. Machine Learning Animated eases you into basic ML concepts and summarizes the learning process in three words: initialize adjust and repeat. This is illustrated step by step with animation to show how machines learn: from initial parameter values to adjusting each step to the final converged parameters and predictions. This book teaches readers to create their own neural networks with dense and convolutional layers and use them to make binary and multi-category classifications. Readers will learn how to build deep learning game strategies and combine this with reinforcement learning witnessing AI achieve super-human performance in Atari games such as Breakout Space Invaders Seaquest and Beam Rider. Written in a clear and concise style illustrated with animations and images this book is particularly appealing to readers with no background in computer science mathematics or statistics. Access the book's repository at: https://github. com/markhliu/MLA

GBP 74.99

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An Introduction to Nonparametric Statistics

An Introduction to Nonparametric Statistics presents techniques for statistical analysis in the absence of strong assumptions about the distributions generating the data. Rank-based and resampling techniques are heavily represented but robust techniques are considered as well. These techniques include one-sample testing and estimation multi-sample testing and estimation and regression. Attention is paid to the intellectual development of the field with a thorough review of bibliographical references. Computational tools in R and SAS are developed and illustrated via examples. Exercises designed to reinforce examples are included. Features Rank-based techniques including sign Kruskal-Wallis Friedman Mann-Whitney and Wilcoxon tests are presented Tests are inverted to produce estimates and confidence intervals Multivariate tests are explored Techniques reflecting the dependence of a response variable on explanatory variables are presented Density estimation is explored The bootstrap and jackknife are discussed This text is intended for a graduate student in applied statistics. The course is best taken after an introductory course in statistical methodology elementary probability and regression. Mathematical prerequisites include calculus through multivariate differentiation and integration and ideally a course in matrix algebra.

GBP 84.99

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Financial Mathematics Two Volume Set

This textbook provides complete coverage of discrete-time financial models that form the cornerstones of financial derivative pricing theory. Unlike similar texts in the field this one presents multiple problem-solving approaches linking related comprehensive techniques for pricing different types of financial derivatives. Key features: In-depth coverage of discrete-time theory and methodology. Numerous fully worked out examples and exercises in every chapter. Mathematically rigorous and consistent yet bridging various basic and more advanced concepts. Judicious balance of financial theory mathematical and computational methods. Guide to Material. This revision contains: Almost 200 pages worth of new material in all chapters. A new chapter on elementary probability theory. An expanded the set of solved problems and additional exercises. Answers to all exercises. This book is a comprehensive self-contained and unified treatment of the main theory and application of mathematical methods behind modern-day financial mathematics. Table of Contents List of Figures and Tables Preface I Introduction to Pricing and Management of Financial Securities 1 Mathematics of Compounding 2 Primer on Pricing Risky Securities 3 Portfolio Management 4 Primer on Derivative Securities II Discrete-Time Modelling 5 Single-Period Arrow–Debreu Models 6 Introduction to Discrete-Time Stochastic Calculus 7 Replication and Pricing in the Binomial Tree Model 8 General Multi-Asset Multi-Period Model Appendices A Elementary Probability Theory B Glossary of Symbols and Abbreviations C Answers and Hints to Exercises References Index Biographies Giuseppe Campolieti is Professor of Mathematics at Wilfrid Laurier University in Waterloo Canada. He has been Natural Sciences and Engineering Research Council postdoctoral research fellow and university research fellow at the University of Toronto. In 1998 he joined the Masters in Mathematical Finance as an instructor and later as an adjunct professor in financial mathematics until 2002. Dr. Campolieti also founded a financial software and consulting company in 1998. He joined Laurier in 2002 as Associate Professor of Mathematics and as SHARCNET Chair in Financial Mathematics. Roman N. Makarov is Associate Professor and Chair of Mathematics at Wilfrid Laurier University. Prior to joining Laurier in 2003 he was an Assistant Professor of Mathematics at Siberian State University of Telecommunications and Informatics and a senior research fellow at the Laboratory of Monte Carlo Methods at the Institute of Computational Mathematics and Mathematical Geophysics in Novosibirsk Russia. | Financial Mathematics Two Volume Set

GBP 130.00

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Introduction to Computational Models with Python

Introduction to Computational Models with Python explains how to implement computational models using the flexible and easy-to-use Python programming language. The book uses the Python programming language interpreter and several packages from the huge Python Library that improve the performance of numerical computing such as the Numpy and Scipy modules. The Python source code and data files are available on the author’s website. The book’s five sections present: An overview of problem solving and simple Python programs introducing the basic models and techniques for designing and implementing problem solutions independent of software and hardware toolsProgramming principles with the Python programming language covering basic programming concepts data definitions programming structures with flowcharts and pseudo-code solving problems and algorithmsPython lists arrays basic data structures object orientation linked lists recursion and running programs under LinuxImplementation of computational models with Python using Numpy with examples and case studies The modeling of linear optimization problems from problem formulation to implementation of computational modelsThis book introduces the principles of computational modeling as well as the approaches of multi- and interdisciplinary computing to beginners in the field. It provides the foundation for more advanced studies in scientific computing including parallel computing using MPI grid computing and other methods and techniques used in high-performance computing.

GBP 44.99

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Doing Meta-Analysis with R A Hands-On Guide

Doing Meta-Analysis with R: A Hands-On Guide serves as an accessible introduction on how meta-analyses can be conducted in R. Essential steps for meta-analysis are covered including calculation and pooling of outcome measures forest plots heterogeneity diagnostics subgroup analyses meta-regression methods to control for publication bias risk of bias assessments and plotting tools. Advanced but highly relevant topics such as network meta-analysis multi-three-level meta-analyses Bayesian meta-analysis approaches and SEM meta-analysis are also covered. A companion R package dmetar is introduced at the beginning of the guide. It contains data sets and several helper functions for the meta and metafor package used in the guide. The programming and statistical background covered in the book are kept at a non-expert level making the book widely accessible. Features• Contains two introductory chapters on how to set up an R environment and do basic imports/manipulations of meta-analysis data including exercises• Describes statistical concepts clearly and concisely before applying them in R• Includes step-by-step guidance through the coding required to perform meta-analyses and a companion R package for the book | Doing Meta-Analysis with R A Hands-On Guide

GBP 74.99

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Knowledge Discovery in Proteomics

Multi-modal representations the lack of complete and consistent domain theories rapid evolution of domain knowledge high dimensionality and large amounts of missing information - these are challenges inherent in modern proteomics. As our understanding of protein structure and function becomes ever more complicated we have reached a point where the actual management of data is a major stumbling block to the interpretation of results from proteomic platforms to knowledge discovery. Knowledge Discovery in Proteomics presents timely authoritative discussions on some of the key issues in high-throughput proteomics exploring examples that represent some of the major challenges of knowledge discovery in the field. The authors focus on five specific domains:Mass spectrometry-based protein analysisProtein-protein interaction network analysisSystematic high-throughput protein crystallizationSystematic integrated analysis of multiple data repositoriesSystems biologyIn each area the authors describe the challenges created by the type of data produced and present potential solutions to the problem of data mining within the domain. They take a systems approach covering individual data and integrating its computational aspects from data preprocessing storage and access to analysis visualization and interpretation. With clear exposition practical examples and rich illustrations this book presents an outstanding overview of this emerging field and builds the background needed for the fruitful exchange of ideas between computational and biological scientists.

GBP 59.99

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Clinical Data Quality Checks for CDISC Compliance Using SAS

Clinical Data Quality Checks for CDISC Compliance using SAS is the first book focused on identifying and correcting data quality and CDISC compliance issues with real-world innovative SAS programming techniques such as Proc SQL metadata and macro programming. Learn to master Proc SQL’s subqueries and summary functions for multi-tasking process. Drawing on his more than 25 years’ experience in the pharmaceutical industry the author provides a unique approach that empowers SAS programmers to take control of data quality and CDISC compliance. This book helps you create a system of SDTM and ADaM checks that can be tracked for continuous improvement. How often have you encountered issues such as missing required variables duplicate records invalid derived variables and invalid sequence of two dates? With the SAS programming techniques introduced in this book you can start to monitor these and more complex data and CDISC compliance issues. With increased standardization in SDTM and ADaM specifications and data values codelist dictionaries can be created for better organization planning and maintenance. This book includes a SAS program to create excel files containing unique values from all SDTM and ADaM variables as columns. In addition another SAS program compares SDTM and ADaM codelist dictionaries with codelists from define. xml specifications. Having tools to automate this process greatly saves time from doing it manually. Features SDTMs and ADaMs Vitals SDTMs and ADaMs Data CDISC Specifications Compliance CDISC Data Compliance Protocol Compliance Codelist Dictionary Compliance

GBP 39.99

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Introduction to Self-Driving Vehicle Technology

This book aims to teach the core concepts that make Self-driving vehicles (SDVs) possible. It is aimed at people who want to get their teeth into self-driving vehicle technology by providing genuine technical insights where other books just skim the surface. The book tackles everything from sensors and perception to functional safety and cybersecurity. It also passes on some practical know-how and discusses concrete SDV applications along with a discussion of where this technology is heading. It will serve as a good starting point for software developers or professional engineers who are eager to pursue a career in this exciting field and want to learn more about the basics of SDV algorithms. Likewise academic researchers technology enthusiasts and journalists will also find the book useful. Key Features: Offers a comprehensive technological walk-through of what really matters in SDV development: from hardware software to functional safety and cybersecurity Written by an active practitioner with extensive experience in series development and research in the fields of Advanced Driver Assistance Systems (ADAS) and Autonomous Driving Covers theoretical fundamentals of state-of-the-art SLAM multi-sensor data fusion and other SDV algorithms. Includes practical information and hands-on material with Robot Operating System (ROS) and Open Source Car Control (OSCC). Provides an overview of the strategies trends and applications which companies are pursuing in this field at present as well as other technical insights from the industry. | Introduction to Self-Driving Vehicle Technology

GBP 48.99

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Introduction to Mathematical Oncology

Introduction to Mathematical Oncology presents biologically well-motivated and mathematically tractable models that facilitate both a deep understanding of cancer biology and better cancer treatment designs. It covers the medical and biological background of the diseases modeling issues and existing methods and their limitations. The authors introduce mathematical and programming tools along with analytical and numerical studies of the models. They also develop new mathematical tools and look to future improvements on dynamical models. After introducing the general theory of medicine and exploring how mathematics can be essential in its understanding the text describes well-known practical and insightful mathematical models of avascular tumor growth and mathematically tractable treatment models based on ordinary differential equations. It continues the topic of avascular tumor growth in the context of partial differential equation models by incorporating the spatial structure and physiological structure such as cell size. The book then focuses on the recent active multi-scale modeling efforts on prostate cancer growth and treatment dynamics. It also examines more mechanistically formulated models including cell quota-based population growth models with applications to real tumors and validation using clinical data. The remainder of the text presents abundant additional historical biological and medical background materials for advanced and specific treatment modeling efforts. Extensively classroom-tested in undergraduate and graduate courses this self-contained book allows instructors to emphasize specific topics relevant to clinical cancer biology and treatment. It can be used in a variety of ways including a single-semester undergraduate course a more ambitious graduate course or a full-year sequence on mathematical oncology.

GBP 44.99

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Unmatched 50 Years of Supercomputing

Unmatched: 50 Years of Supercomputing: A Personal Journey Accompanying the Evolution of a Powerful Tool The rapid and extraordinary progress of supercomputing over the past half-century is a powerful demonstration of our relentless drive to understand and shape the world around us. In this book David Barkai offers a unique and compelling account of this remarkable technological journey drawing from his own rich experiences working at the forefront of high-performance computing (HPC). This book is a journey delineated as five decade-long ‘epochs’ defined by the systems’ architectural themes: vector processors multi-processors microprocessors clusters and accelerators and cloud computing. The final part examines key issues of HPC and discusses where it might be headed. A central goal of this book is to show how computing power has been applied and more importantly how it has impacted and benefitted society. To this end the use of HPC is illustrated in a range of industries and applications from weather and climate modeling to engineering and life sciences. As such this book appeals to both students and general readers with an interest in HPC as well as industry professionals looking to revolutionize their practice. From the Foreword: “David Barkai's career has spanned five decades during which he has had the rare opportunity to be part of some of the most significant developments in the field of supercomputing. His personal and professional insights combined with his deep knowledge and passion for the subject matter make this book an invaluable resource for anyone interested in the evolution of HPC and its impact on our lives. ” -Horst Simon Director Abu Dhabi Investment Authority (ADIA) Lab | Unmatched 50 Years of Supercomputing

GBP 45.99

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SAS Programming The One-Day Course

Aimed at researchers and students SAS Programming: The One-Day Course provides an introduction to the SAS programming language. It gives the reader a start in SAS programming and the basic data manipulations and statistical summaries that are available through SAS. The book has its origins in material prepared by the author for a one-day course in SAS programming and the fact that it has been developed from a training course is reflected in the concise nature of the presentation. Unlike other introductory competitors on the market this is a pocket-sized reference that does not clutter the programming techniques presented by trying to teach statistical techniques at the same time. Strong on explanations of how to carry out data manipulations that real-life data often call for each programming technique is supported by tasks to develop skills and confidence. It also contains tasks for the reader complete with solutions. Datasets and the programming code are available to download from www. crcpress. com/e_products/downloads. Once readers have mastered the topics covered in the book they will be well placed to learn further aspects of SAS programming. | SAS Programming The One-Day Course

GBP 175.00

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Pricing in General Insurance

Based on the syllabus of the actuarial profession courses on general insurance pricing – with additional material inspired by the author’s own experience as a practitioner and lecturer – Pricing in General Insurance Second Edition presents pricing as a formalised process that starts with collecting information about a particular policyholder or risk and ends with a commercially informed rate. The first edition of the book proved very popular among students and practitioners with its pragmatic approach informal style and wide-ranging selection of topics including: Background and context for pricing Process of experience rating ranging from traditional approaches (burning cost analysis) to more modern approaches (stochastic modelling) Exposure rating for both property and casualty products Specialised techniques for personal lines (e. g. GLMs) reinsurance and specific products such as credit risk and weather derivatives General-purpose techniques such as credibility multi-line pricing and insurance optimisation The second edition is a substantial update on the first edition including: New chapter on pricing models: their structure development calibration and maintenance New chapter on rate change calculations and the pricing cycle Substantially enhanced treatment of exposure rating increased limit factors burning cost analysis Expanded treatment of triangle-free techniques for claim count development Improved treatment of premium building and capital allocation Expanded treatment of machine learning Enriched treatment of rating factor selection and the inclusion of generalised additive models The book delivers a practical introduction to all aspects of general insurance pricing and is aimed at students of general insurance and actuarial science as well as practitioners in the field. It is complemented by online material such as spreadsheets which implement the techniques described in the book solutions to problems a glossary and other appendices – increasing the practical value of the book.

GBP 74.99

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GPU Parallel Program Development Using CUDA

GPU Parallel Program Development using CUDA teaches GPU programming by showing the differences among different families of GPUs. This approach prepares the reader for the next generation and future generations of GPUs. The book emphasizes concepts that will remain relevant for a long time rather than concepts that are platform-specific. At the same time the book also provides platform-dependent explanations that are as valuable as generalized GPU concepts. The book consists of three separate parts; it starts by explaining parallelism using CPU multi-threading in Part I. A few simple programs are used to demonstrate the concept of dividing a large task into multiple parallel sub-tasks and mapping them to CPU threads. Multiple ways of parallelizing the same task are analyzed and their pros/cons are studied in terms of both core and memory operation. Part II of the book introduces GPU massive parallelism. The same programs are parallelized on multiple Nvidia GPU platforms and the same performance analysis is repeated. Because the core and memory structures of CPUs and GPUs are different the results differ in interesting ways. The end goal is to make programmers aware of all the good ideas as well as the bad ideas so readers can apply the good ideas and avoid the bad ideas in their own programs. Part III of the book provides pointer for readers who want to expand their horizons. It provides a brief introduction to popular CUDA libraries (such as cuBLAS cuFFT NPP and Thrust) the OpenCL programming language an overview of GPU programming using other programming languages and API libraries (such as Python OpenCV OpenGL and Apple’s Swift and Metal ) and the deep learning library cuDNN.

GBP 44.99

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Computational Optimization Success in Practice

This textbook offers a guided tutorial that reviews the theoretical fundamentals while going through the practical examples used for constructing the computational frame applied to various real-life models. Computational Optimization: Success in Practice will lead the readers through the entire process. They will start with the simple calculus examples of fitting data and basics of optimal control methods and end up constructing a multi-component framework for running PDE-constrained optimization. This framework will be assembled piece by piece; the readers may apply this process at the levels of complexity matching their current projects or research needs. By connecting examples with the theory and discussing the proper communication between them the readers will learn the process of creating a big house. Moreover they can use the framework exemplified in the book as the template for their research or course problems – they will know how to change the single bricks or add extra floors on top of that. This book is for students faculty and researchers. Features The main optimization framework builds through the course exercises and centers on MATLAB® All other scripts to implement computations for solving optimization problems with various models use only open-source software e. g. FreeFEM All computational steps are platform-independent; readers may freely use Windows macOS or Linux systems All scripts illustrating every step in building the optimization framework will be available to the readers online Each chapter contains problems based on the examples provided in the text and associated scripts. The readers will not need to create the scripts from scratch but rather modify the codes provided as a supplement to the book This book will prove valuable to graduate students of math computer science engineering and all who explore optimization techniques at different levels for educational or research purposes. It will benefit many professionals in academic and industry-related research: professors researchers postdoctoral fellows and the personnel of R&D departments. | Computational Optimization Success in Practice

GBP 84.99

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Brand

Merchant

Price (EUR)

Multi-State Survival Models for Interval-Censored Data

Pocket Book of Integrals and Mathematical Formulas

Programming for Hybrid Multi/Manycore MPP Systems

Advanced Studies in Multi-Criteria Decision Making

Quantitative Trading Algorithms Analytics Data Models Optimization

Mathematics of Keno and Lotteries

Evaluating Climate Change Impacts

Parallel Programming for Modern High Performance Computing Systems

Handbook of Approximation Algorithms and Metaheuristics Methologies and Traditional Applications Volume 1

Correspondence Analysis in Practice

CRC Standard Mathematical Tables and Formulas

Machine Learning Animated

An Introduction to Nonparametric Statistics

Financial Mathematics Two Volume Set

Introduction to Computational Models with Python

Doing Meta-Analysis with R A Hands-On Guide

Knowledge Discovery in Proteomics

Clinical Data Quality Checks for CDISC Compliance Using SAS

Introduction to Self-Driving Vehicle Technology

Introduction to Mathematical Oncology

Unmatched 50 Years of Supercomputing

SAS Programming The One-Day Course

Pricing in General Insurance

GPU Parallel Program Development Using CUDA

Computational Optimization Success in Practice

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