Biostatistica in radiologia : Progettare, realizzare e scrivere un lavoro scientifico radiologico = Biostatistics in Radiology: Designing, creating and writing a radiological scientific work
The progressive affirmation of evidence-based medicine requires radiology to make a qualitative leap: from demonstrating the ability to see more and better to demonstrating a significant improvement in the health or quality of life of patients.
Asylum Determination in Europe : Ethnographic Perspectives
The book includes a legal overview of European asylum determination procedures, followed by sections on the diverse actors involved, the means by which they communicate, and the ways in which they make life and death decisions on a daily basis. It offers a contextually rich account that moves beyond doctrinal law to uncover the gaps and variances between formal policy and legislation, and law as actually practiced.
Linear and Generalized Linear Mixed Models and Their Applications
This book covers two major classes of mixed effects models—linear mixed models and generalized linear mixed models—and it presents an up-to-date account of theory and methods in analysis of these models as well as their applications in various fields. It offers a systematic approach to inference about non-Gaussian linear mixed models. Furthermore, it discusses the latest developments and methods in the field, incorporating relevant updates since publication of the first edition. These include advances in high-dimensional linear mixed models in genome-wide association studies (GWAS), advances in inference about generalized linear mixed models with crossed random effects, new methods in mixed model prediction, mixed model selection, and mixed model diagnostics.
Artificial intelligence in the design process : The impact on creativity and team collaboration
Discusses how to include artificial intelligence (AI) systems in the early stages of the design process. Today designers need new tools capable of supporting them in dealing with the increasing project's complexity and empowering their performances and capabilities. AI systems appear to be powerful means to enhance designers' creativity. This assumption was tested in a workshop where sixteen participants collaborated with three AI systems throughout the creative phases of research, sketching, and color selection. Results show that designers can access a broader level of variance and inspiration while reducing the risk of fossilization by triggering lateral thinking through AI-generated data. Therefore, AI could significantly impact the creative phases of the design process if applied consciously. Being AI systems intelligent agents, the book treats the Human-AI collaboration as a collaboration between human agents, proposing a set of guidelines helpful to achieving an efficient partnership with the machine.
Long Memory in Economics
When applying the statistical theory of long range dependent (LRD) processes to economics, the strong complexity of macroeconomic and financial variables, compared to standard LRD processes, becomes apparent. In order to get a better understanding of the behaviour of some economic variables, the book assembles three different strands of long memory analysis: statistical literature on the properties of, and tests for, LRD processes; mathematical literature on the stochastic processes involved; models from economic theory providing plausible micro foundations for the occurence of long memory in economics. Each chapter of the book will give a comprehensive survey of the state of the art and the directions that future developments are likely to take. Taken as a whole the book provides an overview of LRD processes which is accessible to economists, econometricians and statisticians.
Accounting for social and environmental sustainability : A multi-capital approach
Offers an in‑depth examination of multi‑capital accounting, which has already been integrated within the corporate sustainability reporting directive and will follow on from sustainability reporting. the LIFTS model (limits and foundations towards sustainability accounting model) used in this book combines various scientific and practical contributions to develop budgets for environmental impacts and social obligations on an organisational scale. it proposes an accounting mechanism that enables an organization to manage each of its budgets and measure variances between forecast and actual. it provides an introduction to the principles of this model and its conditions of application and describes its implementation in numerous companies.
Le choix bayésien: Principes et pratique
Covers the so-called Bayesian approach to statistical inference and in particular its decision-making aspects. The bases of this axiomatics (choice of the a priori, optimal decisions, tests and regions of confidence) are discussed in detail, as well as more recent openings of Bayesian analysis such as the choice of models, the use of numerical methods. Stochastic approximation (MCMC), the theory of noninformative laws (Berger-Bernardo axioms) and the relation to the classical theory of admissibility. Each chapter is completed by an extensive series of exercises of increasing difficulty and by bibliographical notes on the themes addressed. This book can be used in a Master's program in Applied Mathematics, Biometrics, Econometrics or any other program that uses quantitative information processing techniques. It only requires a basic course in probability theory and mathematical statistics as a preliminary.
Laws of Nature
The book is concerned with the laws of nature and in particular with the laws of physics. The authors discuss three important questions: First, whether the observed regularities are based on strict "laws of nature" that hold rigorously and without any exception. Second, what we call a "law of nature" is studied by comparing this concept with invariance principles, causality principles, teleological principles and means of predicting future events. Finally, on the basis of these investigations the authors treat the ambitious and intricate third question, why the laws of nature hold. Are there rational reasons for this largely unexplained phenomenon? This book addresses students as well as researchers. It will be an excellent reference for those interested in the philosophical foundations of the natural sciences.
Cambridge and Vienna : Frank P. Ramsey and the Vienna Circle
The Institute Vienna Circle held a conference in 2003, Cambridge and Vienna: Frank P. Ramsey and the Vienna Circle, to commemorate the philosophical and scientific work of Frank Plumpton Ramsey (1903-1930). This Ramsey conference provided historical and biographical perspectives on one of the most gifted thinkers of the Twentieth Century.
Benchmarking, Temporal Distribution, and Reconciliation Methods for Time Series
This book discusses the statistical methods most often applied for such adjustments, ranging from ad hoc procedures to regression-based models. The latter are emphasized, because of their clarity, ease of application, and superior results. Each topic is illustrated with many real case examples. In order to facilitate understanding of their properties and limitations of the methods discussed, a real data example, the Canada Total Retail Trade Series, is followed throughout the book.This book brings together the scattered literature on these topics and presents them using a consistent notation and a unifying view.
Asymptotic Theory of Statistics and Probability
An encyclopedic treatment of classic as well as contemporary large sample theory, dealing with both statistical problems and probabilistic issues and tools. It is written in an extremely lucid style, with an emphasis on the conceptual discussion of the importance of a problem and the impact and relevance of the theorems. The book has 34 chapters over a wide range of topics, nearly 600 exercises for practice and instruction, and another 300 worked out examples. It also includes a large compendium of 300 useful inequalities on probability, linear algebra, and analysis that are collected together from numerous sources, as an invaluable reference for researchers in statistics, probability, and mathematics.
Analysis of variance for random models, Vol. 2 : Unbalanced data : Theory, methods, applications, and data analysis
Analysis of variance (ANOVA) models have become widely used tools and play a fundamental role in much of the application of statistics today. In particular, ANOVA models involving random effects have found widespread application to experimental design in a variety of fields requiring measurements of variance, including agriculture, biology, animal breeding, applied genetics, econometrics, quality control, medicine, engineering, and social sciences. This two-volume work is a comprehensive presentation of different methods and techniques for point estimation, interval estimation, and tests of hypotheses for linear models involving random effects. Both Bayesian and repeated sampling procedures are considered. Volume I examines models with balanced data (orthogonal models); Volume II studies models with unbalanced data (nonorthogonal models).
Analysis of integrated and cointegrated time series with R
The analysis of integrated and co-integrated time series can be considered as the main methodology employed in applied econometrics. This book not only introduces the reader to this topic but enables him to conduct the various unit root tests and co-integration methods on his own by utilizing the free statistical programming environment R. The book encompasses seasonal unit roots, fractional integration, coping with structural breaks, and multivariate time series models. The book is enriched by numerous programming examples to artificial and real data so that it is ideally suited as an accompanying text book to computer lab classes.
An R and S-Plus® Companion to Multivariate Analysis
Most data sets collected by researchers are multivariate, and in the majority of cases the variables need to be examined simultaneously to get the most informative results. This requires the use of one or other of the many methods of multivariate analysis, and the use of a suitable software package such as S-PLUS or R. In this book the core multivariate methodology is covered along with some basic theory for each method described. The necessary R and S-PLUS code is given for each analysis in the book, with any differences between the two highlighted.
Advanced Quantum Mechanics
Advanced Quantum Mechanics, the second volume on quantum mechanics by Franz Schwabl, discusses nonrelativistic multi-particle systems, relativistic wave equations and relativistic fields. Characteristic of Schwabl’s work, this volume features a compelling mathematical presentation in which all intermediate steps are derived and where numerous examples for application and exercises help the reader to gain a thorough working knowledge of the subject. The treatment of relativistic wave equations and their symmetries and the fundamentals of quantum field theory lay the foundations for advanced studies in solid-state physics, nuclear and elementary particle physics. This text extends and complements Schwabl’s introductory Quantum Mechanics, which covers nonrelativistic quantum mechanics and offers a short treatment of the quantization of the radiation field. New material has been added to this third edition of Advanced Quantum Mechanics on Bose gases, the Lorentz covariance of the Dirac equation, and the ‘hole theory’ in the chapter "Physical Interpretation of the Solutions to the Dirac Equation."
A History of Parametric Statistical Inference from Bernoulli to Fischer, 1713-1935
This is a history of parametric statistical inference, written by one of the most important historians of statistics of the 20th century, Anders Hald. This book can be viewed as a follow-up to his two most recent books, although this current text is much more streamlined and contains new analysis of many ideas and developments. And unlike his other books, which were encyclopedic by nature, this book can be used for a course on the topic, the only prerequisites being a basic course in probability and statistics.
A Basic Course on Probability Theory
The book develops the necessary background in probability theory underlying diverse treatments of stochastic processes and their wide-ranging applications. Theorems from analysis and measure theory used in the main text are provided in comprehensive appendices, along with their proofs, for ease of reference.
















