Probability and statistics Books
Taylor & Francis Ltd Large Deviations and Idempotent Probability CRC Monographs and Surveys in Pure and Applied Math Hardcover
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£56.04
Taylor & Francis Ltd Deep Learning in Practice
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£74.09
Taylor & Francis SPSS Demystified
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£156.75
Taylor & Francis Ltd A Journey into Open Science and Research Transparency in Psychology
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£32.99
Taylor & Francis Ltd Engineering ProductionGrade Shiny Apps
Book SynopsisFrom the Reviews[This book] contains an excellent blend of both Shiny-specific topics and practical advice from software development that fits in nicely with Shiny apps. You will find many nuggets of wisdom sprinkled throughout these chapters.Eric Nantz, Host of the R-Podcast and the Shiny Developer Series (from the Foreword)[This] book is a gradual and pleasant invitation to the production-ready shiny apps world. It exposes a comprehensive and robust workflow powered by the {golem} package. [It] fills the not yet covered gap between shiny app development and deployment in such a thrilling way that it may be read in one sitting. In the industry world, where processes robustness is a key toward productivity, this book will indubitably have a tremendous impact.David Granjon, Sr. Expert Data Science, NovartisPresented in full color, Engineering Production-Grade ShinTrade Review"ThinkR’s book is a gradual and pleasant invitation to the production-ready shiny apps world. It focuses on the unfortunately too often forgotten general principles necessary to be successful in this quest, before exposing a comprehensive and robust workflow powered by the {golem} package. This books fills the not yet covered gap between shiny app development and deployment in such a thrilling way that it may be read in one sitting. Readers will appreciate the number of exclusive references like {shinypsum}, {gargoyle}, {crrry} and {dockerfiler} that will definitely help them to reach the production-ready graal. In the industry world, where processes robustness is a key toward productivity, this book will indubitably have a tremendous impact." – David Granjon, Sr. Expert Data Science, Novartis"[This book] contains an excellent blend of both Shiny-specific topics … and practical advice from software development that fits in nicely with Shiny apps. You will find many nuggets of wisdom sprinkled throughout these chapters…."– Eric Nantz, Host of the R-Podcast and the Shiny Developer Series (from the Foreword)Table of Contents1. About Successful Shiny Apps. 2. Planning Ahead. 3. Structuring your Project. 4. Introduction to {golem}. 5. The workflow. 6. UX Matters. 7. Don’t rush into coding. 8. Setting up for success with {golem} (#settingupsuccess). 9. Building an “ipsum-app”. 10. Building the app with {golem} 11. Build yourself a safety net. 12. Version Control. 13. Deploy your application. 14. The Need for Optimization. 15. Common Application Caveats. 16. Optimizing {shiny} Code. 17. Using JavaScript. 18. A Gentle Introduction to CSS. Appendix.
£47.49
Taylor & Francis Ltd Data Visualization and Analysis in Second Language Research Second Language Acquisition Research Series
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£128.25
Taylor & Francis A Journey into Open Science and Research Transparency in Psychology
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£128.25
Taylor & Francis Ltd Backseat Driver
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£31.34
Taylor & Francis Ltd Backseat Driver
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£80.74
Taylor & Francis Ltd Engineering Design and Mathematical Modelling Concepts and Applications
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£128.25
Taylor & Francis Ltd Replication and Evidence Factors in Observational Studies Chapman HallCRC Monographs on Statistics and Applied Probability
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£114.00
Taylor & Francis Ltd Theory of Statistical Inference
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£105.00
Taylor & Francis Ltd Parameter Redundancy and Identifiability
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£47.49
Taylor & Francis Ltd An Introduction to Metric Spaces
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£33.99
Taylor & Francis Ltd Quality Engineering Techniques
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£45.99
Taylor & Francis Ltd Optimization with LINGO18
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£92.14
Taylor & Francis Ltd Optimization with LINGO18
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£43.69
Taylor & Francis Ltd Innovative Methods for Rare Disease Drug Development
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£43.69
Taylor & Francis Ltd SAS Coding Primer and Reference Guide
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£50.34
Taylor & Francis Ltd Computational Aspects of Psychometric Methods
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£137.75
Taylor & Francis Ltd Computational Aspects of Psychometric Methods
Book SynopsisThis book covers computational aspects of psychometric methods involved in developing measurement instruments and analyzing measurement data in social sciences. It covers main topics of psychometrics such as validity, reliability, item analysis, and item response theory models. Trade Review"This book is an excellent combination of introductory and recent advanced psychometric developments with implemented and illustrated examples using R. The book is clearly written and covers man different topics but is especially interesting as R code are given so the reader can learn how to perform the described analyses. Several datasets are given, and the examples are well explained to help readers to learn the methods. The methods in the book include, but are not limited to classical test theory, item response theory (IRT), item analysis, and differential item functioning. I highly recommend this book, both as course book when teaching psychometrics but also for researchers who wants to perform advanced analyses."- Marie Wiberg, Professor, Umeå University"This book is both a comprehensive introduction to psychometrics and a practical guide to implement the methods using R. It covers a wide range of topics, always providing real-case applications and the R code needed to analyse the data. Remarkable strengths of the book are the large variety of datasets used as examples and the fine balance between theory and applications. The book is suitable as a textbook for Psychometrics courses, and it can be of interest to researchers as well."- Michela Battauz, Associate Professor, University of Udine."I have been instructionally using the R package ShinyItemAnalysis, written by the lead author and her team, for several years and am pleased to see this book appear. It is written in a manner that is clear and inviting to the reader and the mathematics necessary to understand the text is mostly within the reach of someone who has taken introductory statistics, regression, and categorical data. Similarly, the necessary R is also kept fairly basic. In addition to item response theory (IRT), the text contains content on topics such as regression-based item analysis, item bias, classical test theory, and computerized adaptive testing. As such, it would be an excellent addition to an IRT course using R. An instructor using a different text but needing examples and exercises in R would also benefit, as would a motivated scholar undertaking self-study. In sum, I highly recommend this book."- Jay Verkuilen, Associate Professor, The City University of New York.“This book stands as an exceptional resource for researchers and students with a keen interest in the fields of Psychometrics and measurement, with a thorough, accessible and interactive approach to allow the reader to understand these complex concepts and the tools associated with them. The book tackles a challenging list of topics and provides guidance and explanation on how to grasp all the steps of the analysis using graphical and computational tools. The teaching of the methods is accomplished with the use of well prepared and documented R code and information on packages as well as the ShinyItemAnalysis application. The book is suitable to researchers and students at all levels including researchers new to the fields of measurement and computational psychometrics but also advanced users who are interested in implementing and learning more advanced tools. A well written book with an extensive material for learning and practice.”- Irini Moustaki, Professor in Social Statistics, London School of Economics."Impressively, Martinková and Hladká appeals to a broad audience of researchers, ranging from beginners to experts from a variety of disciplines. They introduce key concepts in psychometrics through both written descriptions and sample code, with interactive companion material in the application ShinyItemAnalysis and on github. Examples draw from a variety of data sets that cover entrance exams, learning assessments, the process of peer review, and peoples’ personalities, among others. I appreciate their helpful approach of starting with the basics—here, analyses such as t-tests, ANOVAs, and classical testing theory—and then move on to more complex ideas like Item Response Theory and Differential Item Functioning analysis. Martinková and Hladká explain the basics for historical reasons, as well as because they can be sufficient; when they cover more complex analyses, they also advise researchers about when those techniques might be necessary. Within each chapter, the authors discuss the underlying analytical problems and concepts, then dive into the mathematics of those concepts, and conclude with practical application of the concepts. In addition to the examples mentioned in the text, the authors include a final section with exercises for each chapter. I recommend Martinková and Hladká for anyone teaching or learning psychometrics."- Rebecca M. Price, Professor, School of Interdisciplinary Arts and Sciences, University of Washington Bothell Table of Contents1. Introduction 2. Validity 3. Internal structure of test and factor analysis 4. Reliability 5. Traditional item analysis 6. Item analysis with regression models 7. Item response theory models 8. More complex IRT models 9. Differential item functioning 10. Outlook on applications and more advanced psychometric topics Appendix A. Introduction to R Appendix B. Descriptive statistics Appendix C. Distributions of random variables Appendix D. Measurement data in ShinyItemAnalysis Appendix E. Exercises
£54.14
Taylor & Francis Ltd TreeBased Methods for Statistical Learning in R
Book SynopsisTree-based Methods for Statistical Learning in R provides a thorough introduction to both individual decision tree algorithms (Part I) and ensembles thereof (Part II). Part I of the book brings several different tree algorithms into focus, both conventional and contemporary. Building a strong foundation for how individual decision trees work will help readers better understand tree-based ensembles at a deeper level, which lie at the cutting edge of modern statistical and machine learning methodology.The book follows up most ideas and mathematical concepts with code-based examples in the R statistical language; with an emphasis on using as few external packages as possible. For example, users will be exposed to writing their own random forest and gradient tree boosting functions using simple for loops and basic tree fitting software (like rpart and party/partykit), and more. The core chapters also end with a detailed section on relevant softwTrade ReviewTree-based algorithms have been a workhorse for data science teams for decades, but the data science field has lacked an all-encompassing review of trees - and their modern variants like XGBoost - until now. Greenwell has written the ultimate guide for tree-based methods: how they work, their pitfalls, and alternative solutions. He puts it all together in a readable and immediately usable book. You're guaranteed to learn new tips and tricks to help your data science team. -Alex Gutman, Director of Data Science, Author: Becoming a Data Head"Here’s a new title that is a “must have” for any data scientist who uses the R language. It’s a wonderful learning resource for tree-based techniques in statistical learning, one that’s become my go-to text when I find the need to do a deep dive into various ML topic areas for my work."Daniel D. Gutierrez, Editor-in-Chief for insideBIGDATA, USA, insideBIGDATA, February 2023Table of Contents1 Introduction 2 Binary recursive partitioning with CART 3 Conditional inference trees 4 "The hitchhiker’s GUIDE to modern decision trees" 5 Ensemble algorithms 6 Peeking inside the “black box”: post-hoc interpretability 7 Random forests 8 Gradient boosting machines
£80.74
Taylor & Francis Ltd SAS Coding Primer and Reference Guide
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£133.00
Taylor & Francis Ltd Supervised Machine Learning
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£45.99
Taylor & Francis Ltd Probability Choice and Reason
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£52.24
Taylor & Francis Ltd Probability Choice and Reason
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£137.75
Taylor & Francis Ltd Spatial Predictive Modeling with R
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£105.00
Taylor & Francis Ltd An Introduction to Acceptance Sampling and SPC with R
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£47.49
Taylor & Francis Ltd Applied Biostatistical Principles and Concepts
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£37.04
Taylor & Francis Ltd Applied Epidemiologic Principles and Concepts
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£37.04
Taylor & Francis Ltd Mathematics and Programming for Machine Learning with R From the Ground Up
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£94.99
Taylor & Francis Ltd Prognostics and Remaining Useful Life RUL
Book SynopsisMaintenance combines various methods, tools, and techniques in a bid to reduce maintenance costs while increasing the reliability, availability, and security of equipment. Condition-based maintenance (CBM) is one such method, and prognostics forms a key element of a CBM program based on mathematical models for predicting remaining useful life (RUL). Prognostics and Remaining Useful Life (RUL) Estimation: Predicting with Confidence compares the techniques and models used to estimate the RUL of different assets, including a review of the relevant literature on prognostic techniques and their use in the industrial field. This book describes different approaches and prognosis methods for different assets backed up by appropriate case studies.FEATURES Presents a compendium of RUL estimation methods and technologies used in predictive maintenance Describes different approaches and prognosis methods for different assets Table of Contents1. Information in Maintenance 2. Predictive Maintenance Programs and Servitization Maintenance as a Service (MaaS) Creating Value through Prognosis Capabilities 3. RUL Estimation Powered by Data-Driven Techniques 4. Context Awareness and Situation Awareness in Prognostics 5. Black Swans and Physics of Failure 6. Hybrid Prognostics Combining Physics-Based and Data-Driven Approaches 7. Prognosis in Prescriptive Analytics 8. Uncertainty Management and the Confidence of RUL Predictions 9. RUL Estimation of Dynamic and Static Assets 10. Principles of Digital Twin 11. Application of Prognosis in Industry, Energy, and Transportation
£166.25
Taylor & Francis Incomparable Values
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£128.25
Taylor & Francis Ltd Simultaneous Global New Drug Development
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£142.50
Taylor & Francis Ltd StateSpace Methods for Time Series Analysis
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£47.49
Taylor & Francis Ltd Weakly Stationary Random Fields Invariant Subspaces and Applications
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£43.69
Taylor & Francis Ltd Stochastic H2H Control
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£42.74
Taylor & Francis Ltd Event Mining
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£42.74
Taylor & Francis Ltd Generalized Sylvester Equations
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£42.74
Taylor & Francis Ltd Statistical Reinforcement Learning
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£42.74
Taylor & Francis Ltd Quantitative Evaluation of Safety in Drug Development
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£43.69
Taylor & Francis Ltd Statistical Inference Based on Divergence Measures
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£43.69
Taylor & Francis Ltd Handbook of Stochastic Analysis and Applications
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£43.69
Taylor & Francis Ltd Multivariate Quality Control
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Taylor & Francis Ltd White Noise Distribution Theory
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£43.69
Taylor & Francis Ltd Truncated and Censored Samples
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Taylor & Francis Ltd Point Processes and Their Statistical Inference
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£45.99
Taylor & Francis Ltd A Primer in Probability
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