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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.
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.
Algorithms in Bioinformatics : Theory and Implementation
Explores a comprehensive and insightful treatment of the practical application of bioinformatic algorithms in a variety of fields. Delivers a fulsome treatment of some of the main algorithms used to explain biological functions and relationships. It introduces readers to the art of algorithms in a practical manner which is linked with biological theory and interpretation. The book covers many key areas of bioinformatics, including global and local sequence alignment, forced alignment, detection of motifs, Sequence logos, Markov chains or information entropy. Other novel approaches are also described, such as Self-Sequence alignment, Objective Digital Stains (ODSs) or Spectral Forecast and the Discrete Probability Detector (DPD) algorithm. Readers will also benefit from the inclusion of: A detailed presentation of new methods, such as Self-sequence alignment, Objective Digital Stains and Spectral Forecast ; A treatment of sequence alignment, including local sequence alignment, global sequence alignment and forced sequence alignment with full implementations ; Discussions of position-specific weight matrices, including the count, weight, relative frequencies, and log-likelihoods matrices ; A detailed presentation of the methods related to Markov Chains as well as a description of their implementation in Bioinformatics and adjacent fields ; An examination of information and entropy, including sequence logos and explanations related to their meaning ; A chapter on philosophical transactions that allows the reader a broader view of the prediction process ; Extensive worked examples with detailed case studies that point out the meaning of different results
Landslide Risk Assessment ; 2nd ed.
Provides guidance to practitioners on establishing the likelihood and extent to which future slope failures could adversely impact society and affect people and property. The only book to focus on risk and landslides, using examples from across the globe, Landslide Risk Assessment examines a variety of approaches to landslide risk assessment and management, introducing the key challenges that practitioners will need to overcome: estimating the probability and consequences of landsliding, combining these to develop a measure of the risk, and making the transition between risk assessment and risk management.
Legitimacy Needs as Drivers of Business Exit
A diversified firm’s withdrawal from a business unit, i.e. business exit, is a significant phenomenon in management practice. Although divestitures are highly relevant in practice, the acquisition of business units attracts much more attention in strategic management research. Carolin Decker develops and empirically applies a framework in which business exits serve the purpose of re-establishing a firm’s previously harmed legitimacy. She suggests four types of legitimacy needs that are to be satisfied with the divestiture of a business unit and the simultaneous pursuit of strategic reorientation. The author tests the theoretical framework with secondary data on 213 business exits. Her findings support the idea that legitimacy needs drive the likelihood of fit-enhancing business exits in divesting firms.
Capital project management ; Vol.2 : Capital project finance
Describes the strategic challenge of adding real economic value, properly and rigorously defined. The author explains how this is accomplished through the capital budgeting process; discusses the importance of free cash flow and finally, capital projects, as financial options, are discussed, as a way to manage risk while enhancing the likelihood of project approval.
Artificial intelligence for business : A roadmap for getting started with AI
Artificial Intelligence for Business: A Roadmap for Getting Started with AI will provide the reader with an easy to understand roadmap for how to take an organization through the adoption of AI technology. It will first help with the identification of which business problems and opportunities are right for AI and how to prioritize them to maximize the likelihood of success. Specific methodologies are introduced to help with finding critical training data within an organization and how to fill data gaps if they exist.
Applications of simulation methods in environmental and resource economics
Simulation methods are revolutionizing the practice of applied economic analysis. This volume collects eighteen chapters written by leading researchers from prestigious research institutions the world over. The common denominator of the papers is their relevance for applied research in environmental and resource economics. The topics range from discrete choice modeling with heterogeneity of preferences, to Bayesian estimation, to Monte Carlo experiments, to structural estimation of Kuhn-Tucker demand systems, to evaluation of simulation noise in maximum simulated likelihood estimates, to dynamic natural resource modeling. Empirical cases are used to show the practical use and the results brought forth by the different methods.
Analysis of microdata
The availability of microdata has increased rapidly over the last decades, and standard statistical and econometric software packages for data analysis include ever more sophisticated modeling options. The goal of this book is to familiarize readers with a wide range of commonly used models, and thereby to enable them to become critical consumers of current empirical research, and to conduct their own empirical analyses.
Linear Models and Generalizations : Least Squares and Alternatives
Gives an up-to-date account of the theory and applications of linear models. The book can be used as a text for courses in statistics at the graduate level and as an accompanying text for courses in other areas. Some of the highlights in this book are as follows. A relatively extensive chapter on matrix theory (Appendix A) provides the necessary tools for proving theorems discussed in the text and offers a selection of classical and modern algebraic results that are useful in research work in econometrics, engineering, and optimization theory. The matrix theory of the last ten years has produced a series of fundamental results aboutthe de?niteness ofmatrices,especially forthe di?erences ofmatrices, which enable superiority comparisons of two biased estimates to be made for the ?rst time. We have attempted to provide a uni?ed theory of inference from linear models with minimal assumptions
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.
A life cycle for clusters? : The dynamics of agglomeration, change, and adaption
The phenomenon of non-random spatial concentrations of firms in one or few related sectors (clusters) is intensively debated in economic theory and policy. The euphoria about successful clusters however neglects that historically, many thriving clusters did deteriorate into old industrial areas. This book studies the determinants of cluster survival by analyzing their adaptability to change in the economic environment. Linking theoretic knowledge with empirical observations, a simulation model (based in the N/K method) is developed, which explains when and why the cluster's architecture assists or hampers adaptability. It is found that architectures with intermediate degrees of division of labour and more collective governance forms foster adaptability. Cluster development is thus path dependent as architectures having evolved over time impact on the likelihood of future survival.
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.
