Model Assessment and Multiresponse Estimation for a Fractionation Model with Coupled Ordinary Differential Equations
Author | : Derrick Keith Rollins |
Publisher | : |
Total Pages | : 188 |
Release | : 1987 |
Genre | : Differential equations |
ISBN | : |
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Author | : Derrick Keith Rollins |
Publisher | : |
Total Pages | : 188 |
Release | : 1987 |
Genre | : Differential equations |
ISBN | : |
Author | : Cihan H. Dagli |
Publisher | : |
Total Pages | : 1296 |
Release | : 1996 |
Genre | : Neural networks (Computer science) |
ISBN | : |
Author | : Kenneth Train |
Publisher | : Cambridge University Press |
Total Pages | : 399 |
Release | : 2009-07-06 |
Genre | : Business & Economics |
ISBN | : 0521766559 |
This book describes the new generation of discrete choice methods, focusing on the many advances that are made possible by simulation. Researchers use these statistical methods to examine the choices that consumers, households, firms, and other agents make. Each of the major models is covered: logit, generalized extreme value, or GEV (including nested and cross-nested logits), probit, and mixed logit, plus a variety of specifications that build on these basics. Simulation-assisted estimation procedures are investigated and compared, including maximum stimulated likelihood, method of simulated moments, and method of simulated scores. Procedures for drawing from densities are described, including variance reduction techniques such as anithetics and Halton draws. Recent advances in Bayesian procedures are explored, including the use of the Metropolis-Hastings algorithm and its variant Gibbs sampling. The second edition adds chapters on endogeneity and expectation-maximization (EM) algorithms. No other book incorporates all these fields, which have arisen in the past 25 years. The procedures are applicable in many fields, including energy, transportation, environmental studies, health, labor, and marketing.
Author | : Thomas J. Santner |
Publisher | : Springer |
Total Pages | : 446 |
Release | : 2019-01-08 |
Genre | : Mathematics |
ISBN | : 1493988476 |
This book describes methods for designing and analyzing experiments that are conducted using a computer code, a computer experiment, and, when possible, a physical experiment. Computer experiments continue to increase in popularity as surrogates for and adjuncts to physical experiments. Since the publication of the first edition, there have been many methodological advances and software developments to implement these new methodologies. The computer experiments literature has emphasized the construction of algorithms for various data analysis tasks (design construction, prediction, sensitivity analysis, calibration among others), and the development of web-based repositories of designs for immediate application. While it is written at a level that is accessible to readers with Masters-level training in Statistics, the book is written in sufficient detail to be useful for practitioners and researchers. New to this revised and expanded edition: • An expanded presentation of basic material on computer experiments and Gaussian processes with additional simulations and examples • A new comparison of plug-in prediction methodologies for real-valued simulator output • An enlarged discussion of space-filling designs including Latin Hypercube designs (LHDs), near-orthogonal designs, and nonrectangular regions • A chapter length description of process-based designs for optimization, to improve good overall fit, quantile estimation, and Pareto optimization • A new chapter describing graphical and numerical sensitivity analysis tools • Substantial new material on calibration-based prediction and inference for calibration parameters • Lists of software that can be used to fit models discussed in the book to aid practitioners
Author | : César de Prada |
Publisher | : MDPI |
Total Pages | : 298 |
Release | : 2019-09-23 |
Genre | : Technology & Engineering |
ISBN | : 3039214551 |
Since process models are nowadays ubiquitous in many applications, the challenges and alternatives related to their development, validation, and efficient use have become more apparent. In addition, the massive amounts of both offline and online data available today open the door for new applications and solutions. However, transforming data into useful models and information in the context of the process industry or of bio-systems requires specific approaches and considerations such as new modelling methodologies incorporating the complex, stochastic, hybrid and distributed nature of many processes in particular. The same can be said about the tools and software environments used to describe, code, and solve such models for their further exploitation. Going well beyond mere simulation tools, these advanced tools offer a software suite built around the models, facilitating tasks such as experiment design, parameter estimation, model initialization, validation, analysis, size reduction, discretization, optimization, distributed computation, co-simulation, etc. This Special Issue collects novel developments in these topics in order to address the challenges brought by the use of models in their different facets, and to reflect state of the art developments in methods, tools and industrial applications.
Author | : Olaf Deutschmann |
Publisher | : John Wiley & Sons |
Total Pages | : 364 |
Release | : 2013-09-18 |
Genre | : Science |
ISBN | : 3527639888 |
The Nobel Prize in Chemistry 2007 awarded to Gerhard Ertl for his groundbreaking studies in surface chemistry highlighted the importance of heterogeneous catalysis not only for modern chemical industry but also for environmental protection. Heterogeneous catalysis is seen as one of the key technologies which could solve the challenges associated with the increasing diversification of raw materials and energy sources. It is the decisive step in most chemical industry processes, a major method of reducing pollutant emissions from mobile sources and is present in fuel cells to produce electricity. The increasing power of computers over the last decades has led to modeling and numerical simulation becoming valuable tools in heterogeneous catalysis. This book covers many aspects, from the state-of-the-art in modeling and simulations of heterogeneous catalytic reactions on a molecular level to heterogeneous catalytic reactions from an engineering perspective. This first book on the topic conveys expert knowledge from surface science to both chemists and engineers interested in heterogeneous catalysis. The well-known and international authors comprehensively present many aspects of the wide bridge between surface science and catalytic technologies, including DFT calculations, reaction dynamics on surfaces, Monte Carlo simulations, heterogeneous reaction rates, reactions in porous media, electro-catalytic reactions, technical reactors, and perspectives of chemical and automobile industry on modeling heterogeneous catalysis. The result is a one-stop reference for theoretical and physical chemists, catalysis researchers, materials scientists, chemical engineers, and chemists in industry who would like to broaden their horizon and get a substantial overview on the different aspects of modeling and simulation of heterogeneous catalytic reactions.
Author | : Gerhard Tutz |
Publisher | : Springer |
Total Pages | : 252 |
Release | : 2016-06-14 |
Genre | : Mathematics |
ISBN | : 3319281585 |
This book focuses on statistical methods for the analysis of discrete failure times. Failure time analysis is one of the most important fields in statistical research, with applications affecting a wide range of disciplines, in particular, demography, econometrics, epidemiology and clinical research. Although there are a large variety of statistical methods for failure time analysis, many techniques are designed for failure times that are measured on a continuous scale. In empirical studies, however, failure times are often discrete, either because they have been measured in intervals (e.g., quarterly or yearly) or because they have been rounded or grouped. The book covers well-established methods like life-table analysis and discrete hazard regression models, but also introduces state-of-the art techniques for model evaluation, nonparametric estimation and variable selection. Throughout, the methods are illustrated by real life applications, and relationships to survival analysis in continuous time are explained. Each section includes a set of exercises on the respective topics. Various functions and tools for the analysis of discrete survival data are collected in the R package discSurv that accompanies the book.
Author | : Stephen A. Sweet |
Publisher | : Allyn & Bacon |
Total Pages | : 0 |
Release | : 2008 |
Genre | : SPSS for Windows |
ISBN | : 9780205483877 |
Accompanying CD-ROM contains data disk to accompany the text.
Author | : Zhi-Fang Fu |
Publisher | : Elsevier |
Total Pages | : 305 |
Release | : 2001-09-04 |
Genre | : Technology & Engineering |
ISBN | : 0080511783 |
Modal Analysis provides a detailed overview of the theory of analytical and experimental modal analysis and its applications. Modal Analysis is the processes of determining the inherent dynamic characteristics of any system and using them to formulate a mathematical model of the dynamic behavior of the system. In the past two decades it has become a major technological tool in the quest for determining, improving and optimizing dynamic characteristics of engineering structures. Its main application is in mechanical and aeronautical engineering, but it is also gaining widespread use in civil and structural engineering, biomechanical problems, space structures, acoustic instruments and nuclear engineering. - The only book to focus on the theory of modal analysis before discussing applications - A relatively new technique being utilized more and more in recent years which is now filtering through to undergraduate courses - Leading expert in the field