Functional Analysis Methods for Reliability Models

This book provides a comprehensive, coherent, and intuitive review of panel data methodologies that are useful for empirical analysis. Substantially revised from the second edition, it includes two new chapters on modeling cross-sectionally dependent data and dynamic systems of equations. Some of the more complicated concepts have been further streamlined. Other new material includes correlated random coefficient models, pseudo-panels, duration and count data models, quantile analysis, and alternative approaches for controlling the impact of unobserved heterogeneity in nonlinear panel data models.

Implementing a novel method for identifying idiolectal co-selections, and taking the UNABOM investigation as a case study, this Pivot evaluates the effectiveness and reliability of using the web for f

This book provides a comprehensive, coherent, and intuitive review of panel data methodologies that are useful for empirical analysis. Substantially revised from the second edition, it includes two new chapters on modeling cross-sectionally dependent data and dynamic systems of equations. Some of the more complicated concepts have been further streamlined. Other new material includes correlated random coefficient models, pseudo-panels, duration and count data models, quantile analysis, and alternative approaches for controlling the impact of unobserved heterogeneity in nonlinear panel data models.

The second volume of this systematical presentation of stochastic approximation methods for models of American-type options presents results on structural studies of optimal stopping domains, Monte Ca

Reflecting the major advances that have been made in the field over the past decade, this book provides an overview of current models of biological systems. The focus is on simple quantitative models, highlighting their role in enhancing our understanding of the strategies of gene regulation and dynamics of information transfer along signalling pathways, as well as in unravelling the interplay between function and evolution. The chapters are self-contained, each describing key methods for studying the quantitative aspects of life through the use of physical models. They focus, in particular, on connecting the dynamics of proteins and DNA with strategic decisions on the larger scale of a living cell, using E. coli and phage lambda as key examples. Encompassing fields such as quantitative molecular biology, systems biology and biophysics, this book will be a valuable tool for students from both biological and physical science backgrounds.

Introducing time series methods and their application in social science research, this practical guide to time series models is the first in the field written for a non-econometrics audience. Giving r

"A comparative analysis of juvenile justice systems, this book features the contributions of international experts. Topics for each country represented include the history of juvenile justice, the nat

This SpringerBrief presents the principles, methods, and workflows for processing and analyzing coastal LiDAR data time-series. Robust methods for computing high resolution digital elevation models (D

Steroid Receptors: Methods and Protocols presents a selection of techniques that have been recently applied to the analysis of steroid receptors, powerful tools for the advancement of our understandin

In Abductive Analysis, Iddo Tavory and Stefan Timmermans provide a new navigational map for theorizing qualitative research. They outline a way to think about observations, methods, and theories that

Written for researchers and graduate students in statistics, demography, and the social sciences, this reference provides an overview of capture-recapture—the statistical methods used to estimate popu

Advanced Computational Vibroacoustics presents an advanced computational method for the prediction of sound and structural vibrations, in low- and medium-frequency ranges - complex structural acoustics and fluid-structure interaction systems encountered in aerospace, automotive, railway, naval, and energy-production industries. The formulations are presented within a unified computational strategy and are adapted for the present and future generation of massively parallel computers. A reduced-order computational model is constructed using the finite element method for the damped structure and the dissipative internal acoustic fluid (gas or liquid with or without free surface) and using an appropriate symmetric boundary-element method for the external acoustic fluid (gas or liquid). This book allows direct access to computational methods that have been adapted for the future evolution of general commercial software. Written for the global market, it is an invaluable resource for academi

Water provides benefits as a commodity for agriculture, industry, and households, and as a public good such as fisheries habitat, water quality and recreational use. To aid in cost-benefit analysis un

Water provides benefits as a commodity for agriculture, industry, and households, and as a public good such as fisheries habitat, water quality and recreational use. To aid in cost-benefit analysis un

Focusing on robust rank-based nonparametric methods, this book covers rank-based fitting and testing for models ranging from simple location models to general linear models for uncorrelated and correl

One of the first to do so, this book integrates the major approaches to APC analysis for aggregate-level data, such as uniform crime reports, vital statistics, and census data. It connects the traditi

By having its origin in analytical and continuum mechanics, as well as in computer science and applied mathematics, multibody dynamics provides a basis for analysis and virtual prototyping of innovati

Simulation of ODE/PDE Models with MATLABR, OCTAVE and SCILAB shows the reader how to exploit a fuller array of numerical methods for the analysis of complex scientific and engineering systems than is

This unique text/reference highlights a selection of practical applications of advanced image analysis methods for medical images. The book covers the complete methodology for processing, analysing an

The Compendium of Organic Synthetic Methods serves as a handy desktop reference for organic chemists to browse new reactions and transformations of interest, facilitating the search for functional gro

This book continues from where the authors' previous book, Structural Proof Theory, ended. It presents an extension of the methods of analysis of proofs in pure logic to elementary axiomatic systems and to what is known as philosophical logic. A self-contained brief introduction to the proof theory of pure logic is included that serves both the mathematically and philosophically oriented reader. The method is built up gradually, with examples drawn from theories of order, lattice theory and elementary geometry. The aim is, in each of the examples, to help the reader grasp the combinatorial behaviour of an axiom system, which typically leads to decidability results. The last part presents, as an application and extension of all that precedes it, a proof-theoretical approach to the Kripke semantics of modal and related logics, with a great number of new results, providing essential reading for mathematical and philosophical logicians.

This book provides a comprehensive overview of calibration and validation techniques for traffic simulation models. It details the data required as an input for the calibration and validation processe

This revised and updated edition focuses on constrained ordination (RDA, CCA), variation partitioning and the use of permutation tests of statistical hypotheses about multivariate data. Both classification and modern regression methods (GLM, GAM, loess) are reviewed and species functional traits and spatial structures analysed. Nine case studies of varying difficulty help to illustrate the suggested analytical methods, using the latest version of Canoco 5. All studies utilise descriptive and manipulative approaches, and are supported by data sets and project files available from the book website: http://regent.prf.jcu.cz/maed2/. Written primarily for community ecologists needing to analyse data resulting from field observations and experiments, this book is a valuable resource to students and researchers dealing with both simple and complex ecological problems, such as the variation of biotic communities with environmental conditions or their response to experimental manipulation.

This rigorous, self-contained book describes mathematical and, in particular, stochastic and graph theoretic methods to assess the performance of complex networks and systems. It comprises three parts: the first is a review of probability theory; Part II covers the classical theory of stochastic processes (Poisson, Markov and queueing theory), which are considered to be the basic building blocks for performance evaluation studies; Part III focuses on the rapidly expanding new field of network science. This part deals with the recently obtained insight that many very different large complex networks – such as the Internet, World Wide Web, metabolic and human brain networks, utility infrastructures, social networks – evolve and behave according to general common scaling laws. This understanding is useful when assessing the end-to-end quality of Internet services and when designing robust and secure networks. Containing problems and solved solutions, the book is ideal for graduate student

Boolean functions are perhaps the most basic objects of study in theoretical computer science. They also arise in other areas of mathematics, including combinatorics, statistical physics, and mathematical social choice. The field of analysis of Boolean functions seeks to understand them via their Fourier transform and other analytic methods. This text gives a thorough overview of the field, beginning with the most basic definitions and proceeding to advanced topics such as hypercontractivity and isoperimetry. Each chapter includes a 'highlight application' such as Arrow's theorem from economics, the Goldreich–Levin algorithm from cryptography/learning theory, Håstad's NP-hardness of approximation results, and 'sharp threshold' theorems for random graph properties. The book includes roughly 450 exercises and can be used as the basis of a one-semester graduate course. It should appeal to advanced undergraduates, graduate students and researchers in computer science theory and related mat

Bayesian Analysis with Stata is written for anyone interested in applying Bayesian methods to real data easily. The book shows how modern analyses based on Markov chain Monte Carlo (MCMC) methods are

Offering a fundamental basis in kernel-based learning theory, this book covers both statistical and algebraic principles. It provides over 30 major theorems for kernel-based supervised and unsupervised learning models. The first of the theorems establishes a condition, arguably necessary and sufficient, for the kernelization of learning models. In addition, several other theorems are devoted to proving mathematical equivalence between seemingly unrelated models. With over 25 closed-form and iterative algorithms, the book provides a step-by-step guide to algorithmic procedures and analysing which factors to consider in tackling a given problem, enabling readers to improve specifically designed learning algorithms, build models for new applications and develop efficient techniques suitable for green machine learning technologies. Numerous real-world examples and over 200 problems, several of which are Matlab-based simulation exercises, make this an essential resource for graduate student

This book reviews and develops Bayesian non-parametric and semi-parametric methods for applications in microeconometrics and quantitative marketing. Most econometric models used in microeconomics and

This is an analysis of the legal rules in the United States for three commercial conflict situations that arise between parties with colliding interests in the same movable property: the protection of

Computer scientists and electrical engineers present an advanced graduate textbook on the main methods, tools, and techniques for microarray image and data analysis. The topics include gridding method

A revolutionary program for developing a toned, muscular body while maximizing athletic abilityEmbracing a spectrum of different workout methods, cross training is the best way to produce a fit, slend

A comprehensive guide to conducting research projects in linguistics, this book provides a complete training in state-of-the-art data collection, processing, and analysis techniques. The book follows the structure of a research project, guiding the reader through the steps involved in collecting and processing data, and providing a solid foundation for linguistic analysis. All major research methods are covered, each by a leading expert. Rather than focusing on narrow specializations, the text fosters interdisciplinarity, with many chapters focusing on shared methods such as sampling, experimental design, transcription and constructing an argument. Highly practical, the book offers helpful tips on how and where to get started, depending on the nature of the research question. The only book that covers the full range of methods used across the field, this student-friendly text is also a helpful reference source for the more experienced researcher and current practitioner.

This modern introduction to seismic data processing in both exploration and global geophysics demonstrates practical applications through real data and tutorial examples. The underlying physics and mathematics of the various seismic analysis methods are presented, giving students an appreciation of their limitations and potential for creating models of the sub-surface. Designed for a one-semester course, this textbook discusses key techniques within the context of the world's ever increasing need for petroleum and mineral resources - equipping upper undergraduate and graduate students with the tools they need for a career in industry. Examples presented throughout the text allow students to compare different methods and can be demonstrated using the instructor's software of choice. Exercises at the end of sections enable students to check their understanding and put the theory into practice and are complemented by solutions for instructors and additional case study examples online to c

A comprehensive guide to conducting research projects in linguistics, this book provides a complete training in state-of-the-art data collection, processing, and analysis techniques. The book follows the structure of a research project, guiding the reader through the steps involved in collecting and processing data, and providing a solid foundation for linguistic analysis. All major research methods are covered, each by a leading expert. Rather than focusing on narrow specializations, the text fosters interdisciplinarity, with many chapters focusing on shared methods such as sampling, experimental design, transcription and constructing an argument. Highly practical, the book offers helpful tips on how and where to get started, depending on the nature of the research question. The only book that covers the full range of methods used across the field, this student-friendly text is also a helpful reference source for the more experienced researcher and current practitioner.

Accessible to quantitative psychology researchers, this book introduces growth curve analysis (GCA) methods for applications in the behavioral sciences. It introduces the challenges involved with this

This text emphasizes nonlinear models for a course in time series analysis. After introducing stochastic processes, Markov chains, Poisson processes, and ARMA models, the authors cover functional auto

Advanced tools for developing new functional materials andapplications in chemical research, pharmaceuticals, and materialsscienceCycloadditions are among the most useful tools for organic chemists, e

A thorough guide to technical analysis methods applied for success in the options marketThough still not widely practiced or accepted in the options market, technical analysis is becoming increasingly

"A brief overview of the global art market precedes an analysis of the various sales venues (auction, commercial gallery, etc.). Library research is reviewed and advanced methods explored. Methods for

'Big data' poses challenges that require both classical multivariate methods and contemporary techniques from machine learning and engineering. This modern text equips you for the new world - integrating the old and the new, fusing theory and practice and bridging the gap to statistical learning. The theoretical framework includes formal statements that set out clearly the guaranteed 'safe operating zone' for the methods and allow you to assess whether data is in the zone, or near enough. Extensive examples showcase the strengths and limitations of different methods with small classical data, data from medicine, biology, marketing and finance, high-dimensional data from bioinformatics, functional data from proteomics, and simulated data. High-dimension low-sample-size data gets special attention. Several data sets are revisited repeatedly to allow comparison of methods. Generous use of colour, algorithms, Matlab code, and problem sets complete the package. Suitable for master's/graduat