Non-Transformational Syntax. Formal and Explicit Models of Grammar

Nonlinear models of elastic and visco-elastic onedimensional continuous structures (beams and cables) are formulated by the authors of this title. Several models of increasing complexity are presented: straight/curved, planar/non-planar, extensible/inextensible, shearable/unshearable, warpingunsensitive/ sensitive, prestressed/unprestressed beams, both in statics and dynamics. Typical engineering problems are solved via perturbation and/or numerical approaches, such as bifurcation and stability under potential and/or tangential loads, parametric excitation, nonlinear dynamics and aeroelasticity. Contents 1. A One-Dimensional Beam Metamodel. 2. Straight Beams. 3. Curved Beams. 4. Internally Constrained Beams. 5. Flexible Cables. 6. Stiff Cables. 7. Locally-Deformable Thin-Walled Beams. 8. Distortion-Constrained Thin-Walled Beams.

The Grammar of Raising and Control surveys analyses across a range of theoretical frameworks from Rosenbaum's classic Standard Theory analysis (1967) to current proposals within the Minimalist Program, and provides readers with a critical understanding of these, helping them in the process to develop keen insights into the strengths and weaknesses of syntactic arguments in general. Distills a very successful graduate course in syntax from two prominent figures in the field, covering analyses from a range of theoretical frameworks. Provides readers with an understanding of the various perspectives represented in generative syntax, using a particular class of grammatical constructions as a means of examining the evolution of syntactic theory over the last thirty years. Helps students to develop keen insights into the strengths and weaknesses of syntactic arguments. Includes excerpts from six important works that allow students to familiarize themselves with the original literature while also providing discussion of the theoretical context in which they were written.

At present the literature gives students and researchers of the very general books on the formal technics. The purpose of this book is to present in a single book, a return of experience on the used of the “formal technics” (such proof and model-checking) on industrial examples for the transportation domain. This book is based on the experience of people which are completely involved in the realization and the evaluation of safety critical system software based. The implication of the industrialists allows to raise the problems of confidentiality which could appear and so allow to supply new useful information (photos, plan of architecture, real example).

A complete guide to the theory and practice of volatility models in financial engineering Volatility has become a hot topic in this era of instant communications, spawning a great deal of research in empirical finance and time series econometrics. Providing an overview of the most recent advances, Handbook of Volatility Models and Their Applications explores key concepts and topics essential for modeling the volatility of financial time series, both univariate and multivariate, parametric and non-parametric, high-frequency and low-frequency. Featuring contributions from international experts in the field, the book features numerous examples and applications from real-world projects and cutting-edge research, showing step by step how to use various methods accurately and efficiently when assessing volatility rates. Following a comprehensive introduction to the topic, readers are provided with three distinct sections that unify the statistical and practical aspects of volatility: Autoregressive Conditional Heteroskedasticity and Stochastic Volatility presents ARCH and stochastic volatility models, with a focus on recent research topics including mean, volatility, and skewness spillovers in equity markets Other Models and Methods presents alternative approaches, such as multiplicative error models, nonparametric and semi-parametric models, and copula-based models of (co)volatilities Realized Volatility explores issues of the measurement of volatility by realized variances and covariances, guiding readers on how to successfully model and forecast these measures Handbook of Volatility Models and Their Applications is an essential reference for academics and practitioners in finance, business, and econometrics who work with volatility models in their everyday work. The book also serves as a supplement for courses on risk management and volatility at the upper-undergraduate and graduate levels.

A valuable overview of the most important ideas and results in statistical modeling Written by a highly-experienced author, Foundations of Linear and Generalized Linear Models is a clear and comprehensive guide to the key concepts and results of linearstatistical models. The book presents a broad, in-depth overview of the most commonly usedstatistical models by discussing the theory underlying the models, R software applications,and examples with crafted models to elucidate key ideas and promote practical modelbuilding. The book begins by illustrating the fundamentals of linear models, such as how the model-fitting projects the data onto a model vector subspace and how orthogonal decompositions of the data yield information about the effects of explanatory variables. Subsequently, the book covers the most popular generalized linear models, which include binomial and multinomial logistic regression for categorical data, and Poisson and negative binomial loglinear models for count data. Focusing on the theoretical underpinnings of these models, Foundations ofLinear and Generalized Linear Models also features: An introduction to quasi-likelihood methods that require weaker distributional assumptions, such as generalized estimating equation methods An overview of linear mixed models and generalized linear mixed models with random effects for clustered correlated data, Bayesian modeling, and extensions to handle problematic cases such as high dimensional problems Numerous examples that use R software for all text data analyses More than 400 exercises for readers to practice and extend the theory, methods, and data analysis A supplementary website with datasets for the examples and exercises An invaluable textbook for upper-undergraduate and graduate-level students in statistics and biostatistics courses, Foundations of Linear and Generalized Linear Models is also an excellent reference for practicing statisticians and biostatisticians, as well as anyone who is interested in learning about the most important statistical models for analyzing data.

Presents an introduction to Bayesian statistics, presents an emphasis on Bayesian methods (prior and posterior), Bayes estimation, prediction, MCMC,Bayesian regression, and Bayesian analysis of statistical modelsof dependence, and features a focus on copulas for risk management Introduction to Bayesian Estimation and Copula Models of Dependence emphasizes the applications of Bayesian analysis to copula modeling and equips readers with the tools needed to implement the procedures of Bayesian estimation in copula models of dependence. This book is structured in two parts: the first four chapters serve as a general introduction to Bayesian statistics with a clear emphasis on parametric estimation and the following four chapters stress statistical models of dependence with a focus of copulas. A review of the main concepts is discussed along with the basics of Bayesian statistics including prior information and experimental data, prior and posterior distributions, with an emphasis on Bayesian parametric estimation. The basic mathematical background of both Markov chains and Monte Carlo integration and simulation is also provided. The authors discuss statistical models of dependence with a focus on copulas and present a brief survey of pre-copula dependence models. The main definitions and notations of copula models are summarized followed by discussions of real-world cases that address particular risk management problems. In addition, this book includes: • Practical examples of copulas in use including within the Basel Accord II documents that regulate the world banking system as well as examples of Bayesian methods within current FDA recommendations • Step-by-step procedures of multivariate data analysis and copula modeling, allowing readers to gain insight for their own applied research and studies • Separate reference lists within each chapter and end-of-the-chapter exercises within Chapters 2 through 8 • A companion website containing appendices: data files and demo files in Microsoft® Office Excel®, basic code in R, and selected exercise solutions Introduction to Bayesian Estimation and Copula Models of Dependence is a reference and resource for statisticians who need to learn formal Bayesian analysis as well as professionals within analytical and risk management departments of banks and insurance companies who are involved in quantitative analysis and forecasting. This book can also be used as a textbook for upper-undergraduate and graduate-level courses in Bayesian statistics and analysis. ARKADY SHEMYAKIN, PhD, is Professor in the Department of Mathematics and Director of the Statistics Program at the University of St. Thomas. A member of the American Statistical Association and the International Society for Bayesian Analysis, Dr. Shemyakin's research interests include informationtheory, Bayesian methods of parametric estimation, and copula models in actuarial mathematics, finance, and engineering. ALEXANDER KNIAZEV, PhD, is Associate Professor and Head of the Department of Mathematics at Astrakhan State University in Russia. Dr. Kniazev's research interests include representation theory of Lie algebras and finite groups, mathematical statistics, econometrics, and financial mathematics.

Presents inference and simulation of stochastic process in the field of model calibration for financial times series modelled by continuous time processes and numerical option pricing. Introduces the bases of probability theory and goes on to explain how to model financial times series with continuous models, how to calibrate them from discrete data and further covers option pricing with one or more underlying assets based on these models. Analysis and implementation of models goes beyond the standard Black and Scholes framework and includes Markov switching models, L?vy models and other models with jumps (e.g. the telegraph process); Topics other than option pricing include: volatility and covariation estimation, change point analysis, asymptotic expansion and classification of financial time series from a statistical viewpoint. The book features problems with solutions and examples. All the examples and R code are available as an additional R package, therefore all the examples can be reproduced.

A practical approach to enhancing quality in software models using UML Version 2.0 «Despite its increasing usage, many companies are not taking the best advantage of UML and, occasionally, individuals have experienced frustration in applying its standards. Perhaps this is because they have not yet read this book!» -From the Foreword by Prof. Brian Henderson-Sellers This book presents a practical checklist approach to enhancing the quality of software models created with the Unified Modeling Language (UML) Version 2.0. The foundation for quality is set by the discussion on the nature and creation of UML models. This is followed by a demonstration of how to apply verification and validation checks to these models with three foci: syntactical correctness, semantic meaningfulness, and aesthetic symmetry. The quality work is carried out within three distinct yet related modeling spaces: * Model of problem space (MOPS) * Model of solution space (MOSS) * Model of background space (MOBS) Readers can then choose a specific quality approach according to their roles in their projects. Verification and validation checks are also organized according to these three modeling spaces, making it easier for the reader to focus on the appropriate diagrams and quality checks corresponding to their modeling space. In addition, a major element of this publication is the Strengths, Weaknesses, Objectives, and Traps (SWOT) analysis. This analysis is performed on each UML diagram, enabling readers to fully comprehend these diagrams, their advantages and limitations, and the way in which they can be used in practical projects for modeling. A consistent case study of the Lucky Insurance System is provided throughout the chapters to illustrate the creation of good quality UML diagrams, followed by application of quality checks to them. With its emphasis on quality in UML-based projects, this book is an essential resource for all quality professionals, including quality analysts, process consultants, quality managers, test designers, and testers.

A practical how-to guide for more effective planningthrough multi-actor modelling Careful planning is the cornerstone of a successful initiative, and any plan, policy, or business strategy can only be successful if it has the support of different actors. These actors may beactively pursuing their own agendas, so the plan must not only offer an optimal solution to theproblem, but must also fit the needs and abilities of the actors involved. Actor and Strategy Models: Practical Applications and Step-wise Approaches provides a primer on multi-actormodelling, based on the fundamental premise that actor strategies are explained by investigatingwhat actors can do, think, and want to achieve. Covering a variety of models with detailed background and case examples, this book focuses on practical application. Step-by-step instructions for each approach provide immediately actionable insight, while a general framework for actor and strategy modelling allows the reader to tailor any approach as needed to optimize results in terms of situation-specific planning. Oriented toward real-world strategy, this helpful resource: • Provides models that shed light on the multi-actor dimensions of planning, using a variety of analytical approaches • Includes literature, theoretical underpinnings, and applications for each method covered • Clarifies the similarities, differences, and suitable applications between various actor modelling approaches • Provides a step-wise framework for actor and strategy modelling • Offers guidance for the identification, structuring, and measuring of values and perceptions • Examines the challenges involved in analyzing actors and strategies Even before planning begins, an endeavor’s success depends upon a clear understanding of the various actors involved in the planning and implementation stages. From game theory and argumentative analysis, through social network analysis, cognitive mapping, and beyond,Actor and Strategy Models provides valuable insight for more effective planning. Leon M. Hermans is an assistant professor at the Faculty of Technology, Policy, and Management at Delft University of Technology. His research focuses on the use of actor analysis methods to support public policy analysis and evaluation. Scott W. Cunningham is an associate professor at the Faculty of Technology, Policy, and Management at Delft University of Technology. He combines work in actor modelling and game theory with research in data mining, technology forecasting, and innovation.

Discover the fundamentals and intricacies of a subject at the interface of chemistry and biology with this authoritative resource

Chemistry and Biology of Non-canonical Nucleic Acids delivers a comprehensive treatment of the chemistry and biology of non-canonical nucleic acids, including their history, structures, stabilities, properties, and functions. You'll learn about the role of these vital compounds in transcription, translation, regulation, telomeres, helicases, cancers, neurodegenerative diseases, therapeutic applications, nanotechnology, and more.

An ideal resource for graduate students, researchers in physical, organic, analytical, and inorganic chemistry will learn about uncommon nucleic acids, become the common non-canonical nucleic acids that fascinate and engage academics and professionals in private industry.

Split into 15 chapters covering a wide range of aspects of non-canonical nucleic acids, the book explains why these compounds exist at the forefront of a new research revolution at the intersection of chemistry and biology. Chemistry and Biology of Non-canonical Nucleic Acids also covers a broad range of topics critical to understanding these versatile and omnipresent chemicals, including:

* A discussion of the dynamic regulation of biosystems by nucleic acids with non-canonical structures
* The role played by nucleic acid structures in neurodegenerative diseases and various cancers
* An exploration of the future outlook for the chemistry and biology of non-canonical nucleic acids
* An introduction to the history of canonical and non-canonical structures of nucleic acids
* An analysis of the physicochemical properties of non-canonical nucleic acids

Perfect for biochemists, materials scientists, and bioengineers, Chemistry and Biology of Non-canonical Nucleic Acids will also earn a place in the libraries of medicinal and pharmaceutical chemists who wish to improve their understanding of life processes and the role that non-canonical nucleic acids play in them.