This is the fifth edition of a very successful textbook on clinical trials methodology, written by recognized leaders who have long and extensive experience in all areas of clinical trials.
This textbook provides the basic concepts of epidemiology while preparing readers with the skills of applying statistical tools in real-life situations.
Take your machine learning skills to the next level by mastering the best framework for uncertainty quantification - Conformal PredictionKey FeaturesMaster Conformal Prediction, a fast-growing ML framework, with Python applications.
This book, written by two mathematicians from the University of Southern California, provides a broad introduction to the important subject of nonlinear mixture models from a Bayesian perspective.
This book provides a comprehensive foundation in Probabilistic Normed (PN) Spaces for anyone conducting research in this field of mathematics and statistics.
There is increasing pressure to protect computer networks against unauthorized intrusion, and some work in this area is concerned with engineering systems that are robust to attack.
These days, an increasing amount of information can be obtained in graphical forms, such as weather maps, soil samples, locations of nests in a breeding colony, microscopical slices, satellite images, radar or medical scans and X-ray techniques.
This important book provides an up-to-date comprehensive and down-to-earth survey of the theory and practice of extreme value distributions - one of the most prominent success stories of modern applied probability and statistics.
This volume consists of research papers dealing with computational and methodological issues of statistical methods on the cutting edge of modern science.
Using a new methodology for foresight studies, this book presents new findings and policy recommendations to improve living conditions and make progress toward achieving the Sustainable Development Goals (SDGs).
Fully updated, this revised edition describes the statistical aspects of both the design and analysis of trials, with particular emphasis on the more recent methods of analysis.
This book provides a comprehensive description of a new method of proving the central limit theorem, through the use of apparently unrelated results from information theory.
Collecting information previously scattered throughout the vast literature, including the author's own research, Stochastic Relations: Foundations for Markov Transition Systems develops the theory of stochastic relations as a basis for Markov transition systems.
Gamblers have been trying to figure out how to game the system since our ancestors first made wagers over dice fashioned from knucklebones: in revolutionary Paris, the 'martingale' strategy was rumoured to lead to foolproof success at roulette ; today, professional gamblers are using cutting-edge techniques to tilt the odds in their favour.
Now in its second edition, this edited book presents recent progress and techniques in partial least squares path modeling (PLS-PM), and provides a comprehensive overview of the current state-of-the-art in PLS-PM research.
'One of the clearest and best-illustrated attempts to explain the virtually inaccessible, the brain' SUNDAY TIMESBrain scans reveal our thoughts, memories - even our moods - as clearly as an X-ray reveals our bones.
Spatial data is crucial to improve decision-making in a wide range of fields including environment, health, ecology, urban planning, economy, and society.
The book comprises original articles on topical issues of risk theory, rational decision making, statistical decisions, and control of stochastic systems.
Focusing on the underlying themes that run through most multivariate methods, in this fully updated 3rd edition of The Essence of Multivariate Thinking Dr.
This book provides a detailed description of the application of mathematical learning curve modeling to analyze the state of learning and memory in humans and animals.
Departing from traditional methodologies of teaching data analysis, this book presents a dual-track learning experience, with both Executive and Technical Tracks, designed to accommodate readers with various learning goals or skill levels.
Introduction to Data Science in Biostatistics: Using R, the Tidyverse Ecosystem, and APIs defines and explores the term "e;data science"e; and discusses the many professional skills and competencies affiliated with the industry.
Artificial Intelligence and Knowledge Processing play a vital role in various automation industries and their functioning in converting traditional industries to AI-based factories.
Bringing together both new and old results, Theory of Factorial Design: Single- and Multi-Stratum Experiments provides a rigorous, systematic, and up-to-date treatment of the theoretical aspects of factorial design.
Drawing on the statistical and philosophical expertise of its authors, this book is designed to improve understanding and use of randomised controlled trials (RCTs) among health professionals.
With the primary goal of expanding access to spatial data science tools, this book offers dozens of minimal or low-code functions and tutorials designed to ease the implementation of fully reproducible Spatial Socio-Econometric Modeling (SSEM) analyses.
Maximum care has been taken in preparing the chapters through the inclusion of different topics, which are commonly discussed by teachers in their lectures.
