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Statistical Inference
Statistical inference is the foundation on which much of statistical practice is built. The book covers the topic at a level suitable for students and professionals who need to understand these foundations.
Uncertain Judgements
Elicitation is the process of extracting expert knowledge about some unknown quantity or quantities, and formulating that information as a probability distribution. Elicitation is important in situations, such as modelling the safety of nuclear installations or assessing the risk of terrorist attacks, where expert knowledge is essentially the only source of good information. It also plays a major role in other contexts by augmenting scarce observational data, through the use of Bayesian statistical methods. However, elicitation is not a simple task, and practitioners need to be aware of a wide range of research findings in order to elicit expert judgements accurately and reliably. Uncertain ...
Principles of Risk Analysis
In every decision context there are things we know and things we do not know. Risk analysis uses science and the best available evidence to assess what we know-and it is intentional in the way it addresses the importance of the things we don't know. Principles of Risk Analysis: Decision Making Under Uncertainty lays out the tasks of risk analysis i
Mathematics and Computation in Music
This book constitutes the thoroughly refereed proceedings of the Fourth International Conference on Mathematics and Computation in Music, MCM 2013, held in Montreal, Canada, in June 2013. The 18 papers presented were carefully reviewed and selected from numerous submissions. They are promoting the collaboration and exchange of ideas among researchers in music theory, mathematics, computer science, musicology, cognition and other related fields.
Recent Advances in Natural Language Processing IV
Printbegrænsninger: Der kan printes 10 sider ad gangen og max. 40 sider pr. session
Design and Analysis of Experiments and Observational Studies using R
Introduction to Design and Analysis of Scientific Studies exposes undergraduate and graduate students to the foundations of classical experimental design and observational studies through a modern framework - The Rubin Causal Model. A causal inference framework is important in design, data collection and analysis since it provides a framework for investigators to readily evaluate study limitations and draw appropriate conclusions. R is used to implement designs and analyse the data collected. Features: Classical experimental design with an emphasis on computation using tidyverse packages in R. Applications of experimental design to clinical trials, A/B testing, and other modern examples. Discussion of the link between classical experimental design and causal inference. The role of randomization in experimental design and sampling in the big data era. Exercises with solutions. Instructor slides in RMarkdown, a new R package will be developed to be used with book, and a bookdown version of the book will be freely available. The proposed book will emphasize ethics, communication and decision making as part of design, data analysis, and statistical thinking.
Expert Judgement in Risk and Decision Analysis
This book pulls together many perspectives on the theory, methods and practice of drawing judgments from panels of experts in assessing risks and making decisions in complex circumstances. The book is divided into four parts: Structured Expert Judgment (SEJ) current research fronts; the contributions of Roger Cooke and the Classical Model he developed; process, procedures and education; and applications. After an Introduction by the Editors, the first part presents chapters on expert elicitation of parameters of multinomial models; the advantages of using performance weighting by advancing the “random expert” hypothesis; expert elicitation for specific graphical models; modelling depende...
Primer on Risk Analysis
In every decision context there are things we know and things we do not know. Risk analysis uses science and the best available evidence to assess what we know-and it is intentional in the way it addresses the importance of the things we don't know. Primer on Risk Analysis: Decision Making Under Uncertainty lays out the tasks of risk analysis in a
Bayesian Analysis in Statistics and Econometrics
This book is a definitive work that captures the current state of knowledge of Bayesian Analysis in Statistics and Econometrics and attempts to move it forward. It covers such topics as foundations, forecasting inferential matters, regression, computation and applications.
Pattern in Music
This book presents analyses of pattern in music from different computational and mathematical perspectives. A central purpose of music analysis is to represent, discover, and evaluate repeated structures within single pieces or within larger corpora of related pieces. In the chapters of this book, music corpora are structured as monophonic melodies, polyphony, or chord sequences. Patterns are represented either extensionally as locations of pattern occurrences in the music, or intensionally as sequences of pitch or chord features, rhythmic profiles, geometric point sets, and logical expressions. The chapters cover both deductive analysis, where music is queried for occurrences of a known pat...
