الصفحة 26
الصفحة 26
Design Patterns for eScience
There is much additional software including many versions of the case study as it gets built up and progressively refactored using design patterns. There will be a home web-site for this book which will contain up-to-date information about the software and other aspects of the case study.
Design of Observational Studies
This book introduction to statistical inference in observational studies and a detailed discussion of the principles that guide the design of observational studies. An observational study is an empiric investigation of effects caused by treatments when randomized experimentation is unethical or infeasible. Observational studies are common in most fields that study the effects of treatments on people, including medicine, economics, epidemiology, education, psychology, political science and sociology. The quality and strength of evidence provided by an observational study is determined largely by its design. Design of Observational Studies is organized into five parts. Chapters 2, 3, and 5 of Part I cover concisely many of the ideas discussed in Rosenbaum’s Observational Studies. Part II discusses the practical aspects of using propensity scores and other tools to create a matched comparison that balances many covariates, and includes an updated chapter on matching in R. In Part III, the concept of design sensitivity is used to appraise the relative ability of competing designs to distinguish treatment effects from biases due to unmeasured covariates. Part IV discusses evidence factors and the computerized construction of more than one comparison group. Part V discusses planning the analysis of an observational study, with particular reference to Sir Ronald Fisher’s striking advice for observational studies: "make your theories elaborate."
Design of adaptive finite Element software : The finite element toolbox ALBERTA
During the last years, scientific computing has become an important research branch located between applied mathematics and applied sciences and engineering. Highly efficient numerical methods are based on adaptive methods, higher order discretizations, fast linear and non-linear iterative solvers, multi-level algorithms, etc. Such methods are integrated in the adaptive finite element software ALBERTA. It is a toolbox for the fast and flexible implementation of efficient software for real life applications, based on modern algorithms. ALBERTA also serves as an environment for improving existent, or developing new numerical methods in an interplay with mathematical analysis and it allows the direct integration of such new or improved methods in existing simulation software.
Design and Analysis of Simulation Experiments
This is an advanced expository book on statistical methods for the Design and Analysis of Simulation Experiments (DASE). Though the book focuses on DASE for discrete-event simulation (such as queuing and inventory simulations), it also discusses DASE for deterministic simulation (such as engineering and physics simulations). The text presents both classic and modern statistical designs. Classic designs (e.g., fractional factorials) assume only a few factors with a few values per factor. The resulting input/output data of the simulation experiment are analyzed through low-order polynomials, which are linear regression (meta)models. Modern designs allow many more factors, possible with many values per factor. These designs include group screening (e.g., Sequential Bifurcation, SB) and space filling designs (e.g., Latin Hypercube Sampling, LHS). The data resulting from these modern designs may be analyzed through low-order polynomials for group screening and various metamodel types (e.g., Kriging) for LHS.
Dependence in Probability and Statistics
This book gives a detailed account of some recent developments in the field of probability and statistics for dependent data. The book covers a wide range of topics from Markov chain theory and weak dependence with an emphasis on some recent developments on dynamical systems, to strong dependence in times series and random fields. A special section is devoted to statistical estimation problems and specific applications. The book is written as a succession of papers by some specialists of the field, alternating general surveys, mostly at a level accessible to graduate students in probability and statistics, and more general research papers mainly suitable to researchers in the field. The first part of the book considers some recent developments on weak dependent time series, including some new results for Markov chains as well as some developments on new notions of weak dependence. This part also intends to fill a gap between the probability and statistical literature and the dynamical system literature. The second part presents some new results on strong dependence with a special emphasis on non-linear processes and random fields currently encountered in applications. Finally, in the last part, some general estimation problems are investigated, ranging from rate of convergence of maximum likelihood estimators to efficient estimation in parametric or non-parametric time series models, with an emphasis on applications with non-stationary data.
Delay Differential Equations and Applications ; Proceedings of the NATO Advanced Study Institute held in Marrakech, Morocco, 9-21 September 2002
This Edition includes detailed discussion and analysis on: General Results and Linear Theory of Delay Equations in Finite Dimensional Spaces; Hopf Bifurcation, Centre Manifolds and Normal Forms for Delay Differential Equations; Functional Differential Equations in Infinite Dimensional Spaces; and Delay Differential Equations and Applications.
Deformations of Algebraic Schemes
This study has become increasingly important in algebraic geometry in every context where variational phenomena come into play, and in classification theory, e.g. the study of the local properties of moduli spaces.Today deformation theory is highly formalized and has ramified widely within mathematics. This self-contained account of deformation theory in classical algebraic geometry (over an algebraically closed field) brings together for the first time some results previously scattered in the literature, with proofs that are relatively little known, yet of everyday relevance to algebraic geometers. Based on Grothendieck's functorial approach it covers formal deformation theory, algebraization, isotriviality, Hilbert schemes, Quot schemes and flag Hilbert schemes. It includes applications to the construction and properties of Severi varieties of families of plane nodal curves, space curves, deformations of quotient singularities, Hilbert schemes of points, local Picard functors, etc. Many examples are provided. Most of the algebraic results needed are proved.
Decision Modeling and Behavior in Complex and Uncertain Environments
Devoted to examining new research at the interface of operations research, behavioral and cognitive sciences, and decision analysis. In these 14 self-contained chapters, four themes emerge, providing the reader with a variety of perspectives both theoretic and applied to meet the challenges of devising models to understand the decision-making process. The main broad topics include: the integration of decision analysis and behavioral models / innovations in behavioral models / exploring descriptive behavior models / experimental studies
Data Science and Classification
This volume provides new methodological developments in data analysis and classification. A wide range of topics is covered that includes the measurement of similarity and dissimilarity, methods for classification and clustering, network and graph analyses, analysis of symbolic data, and web mining. Apart from structural and theoretical results the book shows how to apply the proposed to a variety of problems, for example in medicine, microarray analysis, social network structures, and music. The combination of new methodological advances with the wide range of real applications collected in this volume is of special value for researchers when choosing the appropriate among newly developed analytical tools for their research problems in classification and data analysis.
Data Monitoring in Clinical Trials : A Case Studies Approach
Randomized clinical trials are the gold standard for establishing many clinical practice guidelines and are central to evidence based medicine. Obtaining the best evidence through clinical trials must be done within the boundaries of rigorous science and ethical principles. One fundamental principle is that trials should not continue longer than necessary to reach their objectives. Therefore, trials must be monitored for recruitment progress, quality of data, adherence to patient care or prevention standards, and early evidence of benefit or harm. Frequently, a group of external experts, independent from the investigators and trial sponsor, is charged with this monitoring responsibility, especially for safety and early benefit. This group is referred to by various names, such as a data monitoring committee or a data and safety monitoring board. This book, through a series of case studies presented by many distinguished clinical trial experts, illustrates the complexity of this monitoring process.No other text has as extensive a collection of cases which provide insight into the many issues, often conflicting, that must be examined before recommendations to continue or discontinue a trial can be made. While depth in statistical methods is not required, some familiarity with statistical design and analysis issues in clinical trials is helpful. The cases cover trials which were terminated early for convincing evidence of benefit, or for harmful effects. Cases with complex issues are also included. This series of cases should provide broad background information for potential monitoring committee members and better prepare them for the challenges that may exist in the trials for which they are responsible.
Data Manipulation with R
Since its inception, R has become one of the preeminent programs for statistical computing and data analysis. The ready availability of the program, along with a wide variety of packages and the supportive R community make R an excellent choice for almost any kind of computing task related to statistics. However, many users, especially those with experience in other languages, do not take advantage of the full power of R. Because of the nature of R, solutions that make sense in other languages may not be very efficient in R. This book presents a wide array of methods applicable for reading data into R, and efficiently manipulating that data.
Data Analysis, Classification and the Forward Search ; Proceedings of the Meeting of the Classification and Data Analysis Group (CLADAG) of the Italian Statistical Society, University of Parma, June 6-8, 2005
This book presents new developments in data analysis, classification and multivariate statistics, and in their algorithmic implementation. The volume offers contributions to the theory of clustering and discrimination, multidimensional data analysis, data mining, and robust statistics with a special emphasis on the novel Forward Search approach. Many papers provide significant insight in a wide range of fields of application. Customer satisfaction and service evaluation are two examples of such emerging fields.
Data Analysis Using the Method of Least Squares : Extracting the Most Information from Experiments
The preferred method of data analysis of quantitative experiments is the method of least squares. Often, however, the full power of the method is overlooked and very few books deal with this subject at the level that it deserves. The purpose of Data Analysis Using the Methods of Least Squares is to fill this gap and include the type of information required to help scientists and engineers apply the method to problems in their special fields of interest.Linear and non-linear least squares, the use of experimental error estimates for data weighting, procedures to include prior estimates, methodology for selecting and testing models, prediction analysis, and some non-parametric methods are discussed.
Data Analysis and Decision Support
Presents advances in data analysis and decision support and gives an actual overview on the interface between mathematics, operations research, statistics, computer science, and management science. Areas that receive considerable attention in the book are discrimination and clustering, multidimensional scaling, data mining and more.
Darboux Transformations in Integrable Systems : Theory and their Applications to Geometry
This book presents the Darboux transformations in matrix form and provides purely algebraic algorithms for constructing the explicit solutions. A basis for using symbolic computations to obtain the explicit exact solutions for many integrable systems is established. Moreover, the behavior of simple and multi-solutions, even in multi-dimensional cases, can be elucidated clearly. The method covers a series of important equations such as various kinds of AKNS systems in R1+n, harmonic maps from 2-dimensional manifolds, self-dual Yang-Mills fields and the generalizations to higher dimensional case, theory of line congruences in three dimensions or higher dimensional space etc. All these cases are explained in detail.
Cyclotomic Fields and Zeta Values
Cyclotomic fields have always occupied a central place in number theory, and the so called "main conjecture" on cyclotomic fields is arguably the deepest and most beautiful theorem known about them. It is also the simplest example of a vast array of subsequent, unproven "main conjectures'' in modern arithmetic geometry involving the arithmetic behaviour of motives over p-adic Lie extensions of number fields. These main conjectures are concerned with what one might loosely call the exact formulae of number theory which conjecturally link the special values of zeta and L-functions to purely arithmetic expressions.
Cycle Spaces of Flag Domains : A Complex Geometric Viewpoint
This monograph, divided into four parts, presents a comprehensive treatment and systematic examination of cycle spaces of flag domains. Assuming only a basic familiarity with the concepts of Lie theory and geometry, this work presents a complete structure theory for these cycle spaces, as well as their applications to harmonic analysis and algebraic geometry.
Cycle Representations of Markov Processes
This book provides new insight into Markovian dependence via the cycle decompositions. It presents a systematic account of a class of stochastic processes known as cycle (or circuit) processes - so-called because they may be defined by directed cycles. An important application of this approach is the insight it provides to electrical networks and the duality principle of networks. This edition adds new advances, which reveal wide-ranging interpretations of cycle representations such as homologic decompositions, orthogonality equations, Fourier series, semigroup equations, and disintegration of measures. The text includes chapter summaries as well as a number of detailed illustrations.
Curve e superfici
The book provides an introduction to Differential Geometry of Curves and Surfaces. The theory of curves starts with a discussion of possible definitions of the concept of curve, proving in particular the classification of 1-dimensional manifolds. We then present the classical local theory of parametrized plane and space curves (curves in n-dimensional space are discussed in the complementary material): curvature, torsion, Frenet’s formulas and the fundamental theorem of the local theory of curves. Then, after a self-contained presentation of degree theory for continuous self-maps of the circumference
Current Trends in Nonlinear Systems and Control : In Honor of Petar Kokotovic and Turi Nicosia
This volume is covering many topics in control theory and several different applications. The variety of their research is reflected in this book, which includes contributions from leading experts in the field ranging from mathematics to laboratory experiments.
