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Invariant Descriptive Set Theory

Handbook of Item Response Theory Three Volume Set

Learning Professional Python Two Volume Set

Financial Mathematics Two Volume Set

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
1

Multiplicative Differential Equations Two Volume Set

Multiplicative Differential Equations Two Volume Set

Multiplicative Differential Equations: Volume I is the first part of a comprehensive approach to the subject. It continues a series of books written by the authors on multiplicative geometric approaches to key mathematical topics. This volume begins with a basic introduction to multiplicative differential equations and then moves on to first and second order equations as well as the question of existence and unique of solutions. Each chapter ends with a section of practical problems. The book is accessible to graduate students and researchers in mathematics physics engineering and biology. Multiplicative Differential Equations: Volume 2 is the second part of a comprehensive approach to the subject. It continues a series of books written by the authors on multiplicative geometric approaches to key mathematical topics. This volume is devoted to the theory of multiplicative differential systems. The asymptotic behavior of the solutions of such systems is studied. Stability theory for multiplicative linear and nonlinear systems is introduced and boundary value problems for second order multiplicative linear and nonlinear equations are explored. The authors also present first order multiplicative partial differential equations. Each chapter ends with a section of practical problems. The book is accessible to graduate students and researchers in mathematics physics engineering and biology. | Multiplicative Differential Equations Two Volume Set

GBP 170.00
1

The Theory of Statistical Implicative Analysis Or the Implausibility of Falsehood ... When the Exception Confirms the Rule

The Theory of Statistical Implicative Analysis Or the Implausibility of Falsehood ... When the Exception Confirms the Rule

This book summarizes the methods and concepts of Statistical Implicative Analysis (SIA) created by Régis Gras in the 1980s to study in a new way the behavioural responses of French pupils to mathematics tests. Using a multidimensional non-symmetrical data analysis method SIA crosses a set of subjects or objects with a set of variables. It effectively complements traditional correlational and psychometric methods. SIA through its various extensions is today presented as a broad Artificial Intelligence method aimed at extracting trends and possible causalities in the form of rules from a set of variables. It is based on the unlikeliness of the existence of these relationships i. e. on the relative weakness of their counter-examples compared to what chance alone would produce. It establishes a dual topological relationship between the set of subjects and the set of variables. Many applications of this approach driving forces or crucibles for the development of SIA have concerned and still concern various fields such as didactics evaluation and assessment psychology sociology medicine biology economics art history and others. Key Features: Presents the foundations and representations of SIA Provides extensions of variable sets and subjects Includes a bonus exercise | The Theory of Statistical Implicative Analysis Or the Implausibility of Falsehood . When the Exception Confirms the Rule

GBP 120.00
1

Graphical Methods for Data Analysis

An Illustrated Introduction to Topology and Homotopy Solutions Manual for Part 1 Topology

Formal Methods in Computer Science

A Bridge to Higher Mathematics

A Bridge to Higher Mathematics

A Bridge to Higher Mathematics is more than simply another book to aid the transition to advanced mathematics. The authors intend to assist students in developing a deeper understanding of mathematics and mathematical thought. The only way to understand mathematics is by doing mathematics. The reader will learn the language of axioms and theorems and will write convincing and cogent proofs using quantifiers. Students will solve many puzzles and encounter some mysteries and challenging problems. The emphasis is on proof. To progress towards mathematical maturity it is necessary to be trained in two aspects: the ability to read and understand a proof and the ability to write a proof. The journey begins with elements of logic and techniques of proof then with elementary set theory relations and functions. Peano axioms for positive integers and for natural numbers follow in particular mathematical and other forms of induction. Next is the construction of integers including some elementary number theory. The notions of finite and infinite sets cardinality of counting techniques and combinatorics illustrate more techniques of proof. For more advanced readers the text concludes with sets of rational numbers the set of reals and the set of complex numbers. Topics like Zorn‘s lemma and the axiom of choice are included. More challenging problems are marked with a star. All these materials are optional depending on the instructor and the goals of the course.

GBP 175.00
1

Search Engine Optimization and Marketing A Recipe for Success in Digital Marketing

Search Engine Optimization and Marketing A Recipe for Success in Digital Marketing

Search Engine Optimization and Marketing: A Recipe for Success in Digital Marketing analyzes the web traffic for online promotion that includes search engine optimization and search engine marketing. After careful analysis of the nuances of the semantic web of search engine optimization (SEO) and its practical set up readers can put their best foot forward for SEO setup link-building for SERP establishment various methods with requisite algorithms and programming codes with process inferences. The book offers comprehensive coverage of essential topics including: • The concept of SEM and SEO • The mechanism of crawler program concepts of keywords • Keyword generation tools • Page ranking mechanism and indexing • Concepts of title meta alt tags • Concepts of PPC/PPM/CTR • SEO/SEM strategies • Anchor text and setting up • Query-based search While other books are focused on the traditional explanation of digital marketing theoretical features of SEO and SEM for keyword set up with link-building this book focuses on the practical applications of the above-mentioned concepts for effective SERP generation. Another unique aspect of this book is its abundance of handy workarounds to set up the techniques for SEO a topic too often neglected by other works in the field. This book is an invaluable resource for social media analytics researchers and digital marketing students. | Search Engine Optimization and Marketing A Recipe for Success in Digital Marketing

GBP 105.00
1

Urban Informatics Using Big Data to Understand and Serve Communities

Urban Informatics Using Big Data to Understand and Serve Communities

Urban Informatics: Using Big Data to Understand and Serve Communities introduces the reader to the tools of data management analysis and manipulation using R statistical software. Designed for undergraduate and above level courses this book is an ideal onramp for the study of urban informatics and how to translate novel data sets into new insights and practical tools. The book follows a unique pedagogical approach developed by the author to enable students to build skills by pursuing projects that inspire and motivate them. Each chapter has an Exploratory Data Assignment that prompts readers to practice their new skills on a data set of their choice. These assignments guide readers through the process of becoming familiar with the contents of a novel data set and communicating meaningful insights from the data to others. Key Features: The technical curriculum consists of both data management and analytics including both as needed to become acquainted with and reveal the content of a new data set. Content that is contextualized in real-world applications relevant to community concerns. Unit-level assignments that educators might use as midterms or otherwise. These include Community Experience assignments that prompt students to evaluate the assumptions they have made about their data against real world information. All data sets are publicly available through the Boston Data Portal. | Urban Informatics Using Big Data to Understand and Serve Communities

GBP 48.99
1

Rough Multiple Objective Decision Making

Rough Multiple Objective Decision Making

Under intense scrutiny for the last few decades Multiple Objective Decision Making (MODM) has been useful for dealing with the multiple-criteria decisions and planning problems associated with many important applications in fields including management science engineering design and transportation. Rough set theory has also proved to be an effective mathematical tool to counter the vague description of objects in fields such as artificial intelligence expert systems civil engineering medical data analysis data mining pattern recognition and decision theory. Rough Multiple Objective Decision Making is perhaps the first book to combine state-of-the-art application of rough set theory rough approximation techniques and MODM. It illustrates traditional techniques—and some that employ simulation-based intelligent algorithms—to solve a wide range of realistic problems. Application of rough theory can remedy two types of uncertainty (randomness and fuzziness) which present significant drawbacks to existing decision-making methods so the authors illustrate the use of rough sets to approximate the feasible set and they explore use of rough intervals to demonstrate relative coefficients and parameters involved in bi-level MODM. The book reviews relevant literature and introduces models for both random and fuzzy rough MODM applying proposed models and algorithms to problem solutions. Given the broad range of uses for decision making the authors offer background and guidance for rough approximation to real-world problems with case studies that focus on engineering applications including construction site layout planning water resource allocation and resource-constrained project scheduling. The text presents a general framework of rough MODM including basic theory models and algorithms as well as a proposed methodological system and discussion of future research.

GBP 74.99
1

Empirical Bayes Methods with Applications

An Introduction to Optimization with Applications in Machine Learning and Data Analytics

An Introduction to Optimization with Applications in Machine Learning and Data Analytics

The primary goal of this text is a practical one. Equipping students with enough knowledge and creating an independent research platform the author strives to prepare students for professional careers. Providing students with a marketable skill set requires topics from many areas of optimization. The initial goal of this text is to develop a marketable skill set for mathematics majors as well as for students of engineering computer science economics statistics and business. Optimization reaches into many different fields. This text provides a balance where one is needed. Mathematics optimization books are often too heavy on theory without enough applications; texts aimed at business students are often strong on applications but weak on math. The book represents an attempt at overcoming this imbalance for all students taking such a course. The book contains many practical applications but also explains the mathematics behind the techniques including stating definitions and proving theorems. Optimization techniques are at the heart of the first spam filters are used in self-driving cars play a great role in machine learning and can be used in such places as determining a batting order in a Major League Baseball game. Additionally optimization has seemingly limitless other applications in business and industry. In short knowledge of this subject offers an individual both a very marketable skill set for a wealth of jobs as well as useful tools for research in many academic disciplines. Many of the problems rely on using a computer. Microsoft’s Excel is most often used as this is common in business but Python and other languages are considered. The consideration of other programming languages permits experienced mathematics and engineering students to use MATLAB® or Mathematica and the computer science students to write their own programs in Java or Python. | An Introduction to Optimization with Applications in Machine Learning and Data Analytics

GBP 82.99
1

Operating System Design The Xinu Approach Second Edition

Operating System Design The Xinu Approach Second Edition

An Update of the Most Practical A-to-Z Operating System BookWidely lauded for avoiding the typical black box approach found in other operating system textbooks the first edition of this bestselling book taught readers how an operating system works and explained how to build it from the ground up. Continuing to follow a logical pattern for system design Operating System Design: The Xinu Approach Second Edition removes the mystery from operating system design and consolidates the body of material into a systematic discipline. It presents a hierarchical design paradigm that organizes major operating system components in an orderly understandable manner. The book guides readers through the construction of a conventional process-based operating system using practical straightforward primitives. It gives the implementation details of one set of primitives usually the most popular set. Once readers understand how primitives can be implemented on conventional hardware they can then easily implement alternative versions. The text begins with a bare machine and proceeds step-by-step through the design and implementation of Xinu which is a small elegant operating system that supports dynamic process creation dynamic memory allocation network communication local and remote file systems a shell and device-independent I/O functions. The Xinu code runs on many hardware platforms. This second edition has been completely rewritten to contrast operating systems for RISC and CISC processors. Encouraging hands-on experimentation the book provides updated code throughout and examples for two low-cost experimenter boards: BeagleBone Black from ARM and Galileo from Intel. | Operating System Design The Xinu Approach Second Edition

GBP 39.99
1

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

Your Essential Guide to Quantitative Hedge Fund Investing

Acceptance Sampling in Quality Control

Smooth Manifolds and Fibre Bundles with Applications to Theoretical Physics

Spectral Theory and Nonlinear Functional Analysis

Software Engineering Practice A Case Study Approach

Software Engineering Practice A Case Study Approach

This book is a broad discussion covering the entire software development lifecycle. It uses a comprehensive case study to address each topic and features the following: A description of the development by the fictional company Homeowner of the DigitalHome (DH) System a system with smart devices for controlling home lighting temperature humidity small appliance power and security A set of scenarios that provide a realistic framework for use of the DH System material Just-in-time training: each chapter includes mini tutorials introducing various software engineering topics that are discussed in that chapter and used in the case study A set of case study exercises that provide an opportunity to engage students in software development practice either individually or in a team environment. Offering a new approach to learning about software engineering theory and practice the text is specifically designed to: Support teaching software engineering using a comprehensive case study covering the complete software development lifecycle Offer opportunities for students to actively learn about and engage in software engineering practice Provide a realistic environment to study a wide array of software engineering topics including agile development Software Engineering Practice: A Case Study Approach supports a student-centered active learning style of teaching. The DH case study exercises provide a variety of opportunities for students to engage in realistic activities related to the theory and practice of software engineering. The text uses a fictitious team of software engineers to portray the nature of software engineering and to depict what actual engineers do when practicing software engineering. All the DH case study exercises can be used as team or group exercises in collaborative learning. Many of the exercises have specific goals related to team building and teaming skills. The text also can be used to support the professional development or certification of practicing software engineers. The case study exercises can be integrated with presentations in a workshop or short course for professionals. | Software Engineering Practice A Case Study Approach

GBP 66.99
1

Generalized Additive Models An Introduction with R Second Edition

Statistical and Econometric Methods for Transportation Data Analysis

Statistical and Econometric Methods for Transportation Data Analysis

The book's website (with databases and other support materials) can be accessed here. Praise for the Second Edition: The second edition introduces an especially broad set of statistical methods … As a lecturer in both transportation and marketing research I find this book an excellent textbook for advanced undergraduate Master’s and Ph. D. students covering topics from simple descriptive statistics to complex Bayesian models. … It is one of the few books that cover an extensive set of statistical methods needed for data analysis in transportation. The book offers a wealth of examples from the transportation field. —The American Statistician Statistical and Econometric Methods for Transportation Data Analysis Third Edition offers an expansion over the first and second editions in response to the recent methodological advancements in the fields of econometrics and statistics and to provide an increasing range of examples and corresponding data sets. It describes and illustrates some of the statistical and econometric tools commonly used in transportation data analysis. It provides a wide breadth of examples and case studies covering applications in various aspects of transportation planning engineering safety and economics. Ample analytical rigor is provided in each chapter so that fundamental concepts and principles are clear and numerous references are provided for those seeking additional technical details and applications. New to the Third Edition Updated references and improved examples throughout. New sections on random parameters linear regression and ordered probability models including the hierarchical ordered probit model. A new section on random parameters models with heterogeneity in the means and variances of parameter estimates. Multiple new sections on correlated random parameters and correlated grouped random parameters in probit logit and hazard-based models. A new section discussing the practical aspects of random parameters model estimation. A new chapter on Latent Class Models. A new chapter on Bivariate and Multivariate Dependent Variable Models. Statistical and Econometric Methods for Transportation Data Analysis Third Edition can serve as a textbook for advanced undergraduate Masters and Ph. D. students in transportation-related disciplines including engineering economics urban and regional planning and sociology. The book also serves as a technical reference for researchers and practitioners wishing to examine and understand a broad range of statistical and econometric tools required to study transportation problems.

GBP 69.99
1

Mathematical Modelling with Differential Equations