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ANOVA and Mixed Models A Short Introduction Using R

ANOVA and Mixed Models A Short Introduction Using R

ANOVA and Mixed Models: A Short Introduction Using R provides both the practitioner and researcher a compact introduction to the analysis of data from the most popular experimental designs. Based on knowledge from an introductory course on probability and statistics the theoretical foundations of the most important models are introduced. The focus is on an intuitive understanding of the theory common pitfalls in practice and the application of the methods in R. From data visualization and model fitting up to the interpretation of the corresponding output the whole workflow is presented using R. The book does not only cover standard ANOVA models but also models for more advanced designs and mixed models which are common in many practical applications. Features Accessible to readers with a basic background in probability and statistics Covers fundamental concepts of experimental design and cause-effect relationships Introduces classical ANOVA models including contrasts and multiple testing Provides an example-based introduction to mixed models Features basic concepts of split-plot and incomplete block designs R code available for all steps Supplementary website with additional resources and updates are available here. This book is primarily aimed at students researchers and practitioners from all areas who wish to analyze corresponding data with R. Readers will learn a broad array of models hand-in-hand with R including the applications of some of the most important add-on packages. | ANOVA and Mixed Models A Short Introduction Using R

GBP 49.99
1

Basic Matrix Algebra with Algorithms and Applications

Fundamentals of Internet of Things

Fundamentals of Internet of Things

The Internet of Things (IoT) networks have revolutionized the world and have innumerable real-time applications on automation. A few examples include driverless cars remote monitoring of the elderly remote order of tea or coffee of your choice from a vending machine and home/industrial automation amongst others. Fundamentals of Internet of Things build the foundations of IoT networks by leveraging the relevant concepts from signal processing communications net-works and machine learning. The book covers two fundamental components of IoT networks namely the Internet and Things. In particular the book focuses on networking concepts protocols clustering data fusion localization energy harvesting control optimization data analytics fog computing privacy and security including elliptic curve cryptography and blockchain technology. Most of the existing books are theoretical and without many mathematical details and examples. In addition some essential topics of the IoT networks are also missing in the existing books. Features: • The book covers cutting-edge research topics• Provides mathematical understanding of the topics in addition to relevant theory and insights• Includes illustrations with hand-solved numerical examples for visualization of the theory and testing of understanding• Lucid and crisp explanation to lessen the study time of the reader The book is a complete package of the fundamentals of IoT networks and is suitable for graduate-level students and researchers who want to dive into the world of IoT networks.

GBP 145.00
1

Introduction to Self-Driving Vehicle Technology

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
1

Algorithms for Next-Generation Sequencing

Big Data Algorithms Analytics and Applications

Big Data Algorithms Analytics and Applications

As today’s organizations are capturing exponentially larger amounts of data than ever now is the time for organizations to rethink how they digest that data. Through advanced algorithms and analytics techniques organizations can harness this data discover hidden patterns and use the newly acquired knowledge to achieve competitive advantages. Presenting the contributions of leading experts in their respective fields Big Data: Algorithms Analytics and Applications bridges the gap between the vastness of Big Data and the appropriate computational methods for scientific and social discovery. It covers fundamental issues about Big Data including efficient algorithmic methods to process data better analytical strategies to digest data and representative applications in diverse fields such as medicine science and engineering. The book is organized into five main sections:Big Data Management—considers the research issues related to the management of Big Data including indexing and scalability aspectsBig Data Processing—addresses the problem of processing Big Data across a wide range of resource-intensive computational settingsBig Data Stream Techniques and Algorithms—explores research issues regarding the management and mining of Big Data in streaming environmentsBig Data Privacy—focuses on models techniques and algorithms for preserving Big Data privacyBig Data Applications—illustrates practical applications of Big Data across several domains including finance multimedia tools biometrics and satellite Big Data processingOverall the book reports on state-of-the-art studies and achievements in algorithms analytics and applications of Big Data. It provides readers with the basis for further efforts in this challenging scientific field that will play a leading role in next-generation database data warehousing data mining and cloud computing research. It also explores related applications in diverse sectors covering technologies for media/data communication elastic media/data storage cross-network media/data fusion and SaaS. | Big Data Algorithms Analytics and Applications

GBP 44.99
1

Grothendieck Construction of Bipermutative-Indexed Categories

Grothendieck Construction of Bipermutative-Indexed Categories

The Grothendieck construction provides an explicit link between indexed categories and opfibrations. It is a fundamental concept in category theory and related fields with far-reaching applications. Bipermutative categories are categorifications of rings. They play a central role in algebraic K-theory and infinite loop space theory. This monograph is a detailed study of the Grothendieck construction over a bipermutative category in the context of categorically enriched multicategories with new and important applications to inverse K-theory and pseudo symmetric E∞-algebras. After carefully recalling preliminaries in enriched categories bipermutative categories and enriched multicategories we show that the Grothendieck construction over a small tight bipermutative category is a pseudo symmetric Cat-multifunctor and generally not a Cat-multifunctor in the symmetric sense. Pseudo symmetry of Cat-multifunctors is a new concept we introduce in this work. The following features make it accessible as a graduate text or reference for experts: Complete definitions and proofs Self-contained background. Parts of Chapters 1–3 7 9 and 10 contain background material from the research literature Extensive cross-references Connections between chapters. Each chapter has its own introduction discussing not only the topics of that chapter but also its connection with other chapters Open questions. Appendix A contains open questions that arise from the material in the text and are suitable for graduate students This book is suitable for graduate students and researchers with an interest in category theory algebraic K-theory homotopy theory and related fields. The presentation is thorough and self-contained with complete details and background material for non-expert readers. | Grothendieck Construction of Bipermutative-Indexed Categories

GBP 110.00
1

Correspondence Analysis in Practice

R Markdown Cookbook

A Concise Introduction to Statistical Inference

An Introduction to Scientific Computing with MATLAB and Python Tutorials

Concise Encyclopedia of Coding Theory

Statistics in Toxicology Using R

Temporal Data Mining

Structured Credit Portfolio Analysis Baskets and CDOs

Fundamentals of Parallel Multicore Architecture

Fundamentals of Parallel Multicore Architecture

Although multicore is now a mainstream architecture there are few textbooks that cover parallel multicore architectures. Filling this gap Fundamentals of Parallel Multicore Architecture provides all the material for a graduate or senior undergraduate course that focuses on the architecture of multicore processors. The book is also useful as a reference for professionals who deal with programming on multicore or designing multicore chips. The text’s coverage of fundamental topics prepares students to study research papers in the multicore architecture area. The text offers many pedagogical features including:Sufficiently short chapters that can be comfortably read over a weekendIntroducing each concept by first describing the problem and building intuition that leads to the need for the conceptDid you know? boxes that present mini case studies alternative points of view examples and other interesting facts or discussion itemsThought-provoking interviews with experts who share their perspectives on multicore architectures in the past present and futureOnline programming assignments and solutions that enhance students’ understandingThe first several chapters address programming issues in shared memory multiprocessors such as the programming model and techniques to parallelize regular and irregular applications. The core of the book covers the architectures for shared memory multiprocessors. The final chapter contains interviews with experts in parallel multicore architecture.

GBP 44.99
1

Algebra & Geometry An Introduction to University Mathematics

Design of Experiments An Introduction Based on Linear Models

Design of Experiments An Introduction Based on Linear Models

Offering deep insight into the connections between design choice and the resulting statistical analysis Design of Experiments: An Introduction Based on Linear Models explores how experiments are designed using the language of linear statistical models. The book presents an organized framework for understanding the statistical aspects of experimental design as a whole within the structure provided by general linear models rather than as a collection of seemingly unrelated solutions to unique problems. The core material can be found in the first thirteen chapters. These chapters cover a review of linear statistical models completely randomized designs randomized complete blocks designs Latin squares analysis of data from orthogonally blocked designs balanced incomplete block designs random block effects split-plot designs and two-level factorial experiments. The remainder of the text discusses factorial group screening experiments regression model design and an introduction to optimal design. To emphasize the practical value of design most chapters contain a short example of a real-world experiment. Details of the calculations performed using R along with an overview of the R commands are provided in an appendix. This text enables students to fully appreciate the fundamental concepts and techniques of experimental design as well as the real-world value of design. It gives them a profound understanding of how design selection affects the information obtained in an experiment. | Design of Experiments An Introduction Based on Linear Models

GBP 74.99
1

Statistical Design and Analysis of Stability Studies

Statistical Design and Analysis of Stability Studies

The US Food and Drug Administration's Report to the Nation in 2004 and 2005 indicated that one of the top reasons for drug recall was that stability data did not support existing expiration dates. Pharmaceutical companies conduct stability studies to characterize the degradation of drug products and to estimate drug shelf life. Illustrating how stability studies play an important role in drug safety and quality assurance Statistical Design and Analysis of Stability Studies presents the principles and methodologies in the design and analysis of stability studies. After introducing the basic concepts of stability testing the book focuses on short-term stability studies and reviews several methods for estimating drug expiration dating periods. It then compares some commonly employed study designs and discusses both fixed and random batch statistical analyses. Following a chapter on the statistical methods for stability analysis under a linear mixed effects model the book examines stability analyses with discrete responses multiple components and frozen drug products. In addition the author provides statistical methods for dissolution testing and explores current issues and recent developments in stability studies. To ensure the safety of consumers professionals in the field must carry out stability studies to determine the reliability of drug products during their expiration period. This book provides the material necessary for you to perform stability designs and analyses in pharmaceutical research and development.

GBP 44.99
1

Measuring Society

Essentials Engineering Mathematics

Essentials Engineering Mathematics

First published in 1992 Essentials of Engineering Mathematics is a widely popular reference ideal for self-study review and fast answers to specific questions. While retaining the style and content that made the first edition so successful the second edition provides even more examples new material and most importantly an introduction to using two of the most prevalent software packages in engineering: Maple and MATLAB. Specifically this edition includes:Introductory accounts of Maple and MATLAB that offer a quick start to using symbolic software to perform calculations explore the properties of functions and mathematical operations and generate graphical outputNew problems involving the mean value theorem for derivativesExtension of the account of stationary points of functions of two variablesThe concept of the direction field of a first-order differential equationIntroduction to the delta function and its use with the Laplace transformThe author includes all of the topics typically covered in first-year undergraduate engineering mathematics courses organized into short easily digestible sections that make it easy to find any subject of interest. Concise right-to-the-point exposition a wealth of examples and extensive problem sets at the end each chapter-with answers at the end of the book-combine to make Essentials of Engineering Mathematics Second Edition ideal as a supplemental textbook for self-study and as a quick guide to fundamental concepts and techniques. | Essentials Engineering Mathematics

GBP 180.00
1

Machine Learning Theory and Practice

Machine Learning Theory and Practice

Machine Learning: Theory and Practice provides an introduction to the most popular methods in machine learning. The book covers regression including regularization tree-based methods including Random Forests and Boosted Trees Artificial Neural Networks including Convolutional Neural Networks (CNNs) reinforcement learning and unsupervised learning focused on clustering. Topics are introduced in a conceptual manner along with necessary mathematical details. The explanations are lucid illustrated with figures and examples. For each machine learning method discussed the book presents appropriate libraries in the R programming language along with programming examples. Features: Provides an easy-to-read presentation of commonly used machine learning algorithms in a manner suitable for advanced undergraduate or beginning graduate students and mathematically and/or programming-oriented individuals who want to learn machine learning on their own. Covers mathematical details of the machine learning algorithms discussed to ensure firm understanding enabling further exploration Presents worked out suitable programming examples thus ensuring conceptual theoretical and practical understanding of the machine learning methods. This book is aimed primarily at introducing essential topics in Machine Learning to advanced undergraduates and beginning graduate students. The number of topics has been kept deliberately small so that it can all be covered in a semester or a quarter. The topics are covered in depth within limits of what can be taught in a short period of time. Thus the book can provide foundations that will empower a student to read advanced books and research papers. | Machine Learning Theory and Practice

GBP 110.00
1

Encyclopedia of Knot Theory

Encyclopedia of Knot Theory

Knot theory is a fascinating mathematical subject with multiple links to theoretical physics. This enyclopedia is filled with valuable information on a rich and fascinating subject. – Ed Witten Recipient of the Fields Medal I spent a pleasant afternoon perusing the Encyclopedia of Knot Theory. It’s a comprehensive compilation of clear introductions to both classical and very modern developments in the field. It will be a terrific resource for the accomplished researcher and will also be an excellent way to lure students both graduate and undergraduate into the field. – Abigail Thompson Distinguished Professor of Mathematics at University of California Davis Knot theory has proven to be a fascinating area of mathematical research dating back about 150 years. Encyclopedia of Knot Theory provides short interconnected articles on a variety of active areas in knot theory and includes beautiful pictures deep mathematical connections and critical applications. Many of the articles in this book are accessible to undergraduates who are working on research or taking an advanced undergraduate course in knot theory. More advanced articles will be useful to graduate students working on a related thesis topic to researchers in another area of topology who are interested in current results in knot theory and to scientists who study the topology and geometry of biopolymers. Features Provides material that is useful and accessible to undergraduates postgraduates and full-time researchers Topics discussed provide an excellent catalyst for students to explore meaningful research and gain confidence and commitment to pursuing advanced degrees Edited and contributed by top researchers in the field of knot theory

GBP 47.95
1

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
1

Mathematical Modeling using Fuzzy Logic Applications to Sustainability

Mathematical Modeling using Fuzzy Logic Applications to Sustainability

Mathematical Modeling using Fuzzy Logic has been a dream project for the author. Fuzzy logic provides a unique method of approximate reasoning in an imperfect world. This text is a bridge to the principles of fuzzy logic through an application-focused approach to selected topics in engineering and management. The many examples point to the richer solutions obtained through fuzzy logic and to the possibilities of much wider applications.  There are relatively very few texts available at present in fuzzy logic applications. The style and content of this text is complementary to those already available. New areas of application like application of fuzzy logic in modeling of sustainability are presented in a graded approach in which the underlying concepts are first described. The text is broadly divided into two parts: the first treats processes materials and system applications related to fuzzy logic and the second delves into the modeling of sustainability with the help of fuzzy logic. This book offers comprehensive coverage of the most essential topics including: Treating processes materials system applications related to fuzzy logic Highlighting new areas of application of fuzzy logic Identifying possibilities of much wider applications of fuzzy logic Modeling of sustainability with the help of fuzzy logic The level enables a selection of the text to be made for the substance of undergraduate- graduate- and postgraduate-level courses. There is also sufficient volume and quality for the basis of a postgraduate course. A more restricted and judicious selection can provide the material for a professional short course and various university-level courses. | Mathematical Modeling using Fuzzy Logic Applications to Sustainability

GBP 105.00
1