Modelling methods

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  • Modelling methods are now well established in physical, biomedical and engineering sciences; and are widely used in assisting the interpretation of experimental data and increasingly in a predictive mode. Applications to inorganic materials are widespread, and indeed, such methods now play a major role in modelling structures, properties and reactivities of these materials.

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  • Most of the objects in the Excel Object Model have objects with associated collections. The collection object is usually the plural form of the associated object. For example, theWorksheets collection holds a collection ofWorksheet objects. For simplicity, each object and associated collection will be grouped together under the same heading.

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  • This paper proposes a novel method for learning probability models of subcategorization preference of verbs. We consider the issues of case dependencies and noun class generalization in a uniform way by employing the maximum entropy modeling method. We also propose a new model selection algorithm which starts from the most general model and gradually examines more specific models.

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  • Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành y học dành cho các bạn tham khảo đề tài: Estimation of realized heritability in a selected population using mixed model methods

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  • While the stochastic volatility (SV) generalization has been shown to improve the explanatory power over the Black-Scholes model, empirical implications of SV models on option pricing have not yet been adequately tested. The purpose of this paper is to first estimate a multivariate SV model using the efficient method of moments (EMM) technique from observations of underlying state variables and then investigate the respective effect of stochastic interest rates, systematic volatility and idiosyncratic volatility on option prices....

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  • When asked why they tackled Mount Everest, climbers typically reply “Because it was there”. Our motivation for writing Advanced Modelling in Finance is for exactly the opposite reason. There were then, and still are now, almost no books that give due prominence to and explanation of the use of VBA functions within Excel. There is an almost similar lack of books that capture the true vibrant spirit of numerical methods in finance.

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  • The immediate reason for the creation of this book has been the advent of Basel II. This has forced many institutions with loan portfolios into building risk models, and, as a consequence, a need has arisen to have these models validated both internally and externally. What is surprising is that there is very little written that could guide consultants in carrying out these validations. This book aims to fill that gap.

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  • Monte Carlo methods are ubiquitous in applications in the finance and insurance industry. They are often the only accessible tool for financial engineers and actuaries when it comes to complicated price or risk computations, in particular for those that are based on many underlyings. However, as they tend to be slow, it is very important to have a big tool box for speeding them up or – equivalently – for increasing their accuracy. Further, recent years have seen a lot of developments in Monte Carlo methods with a high potential for success in applications.

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  • Analyze tabular data using the BI Semantic Model (BISM) in Microsoft® SQL Server® 2012 Analysis Services—and discover a simpler method for creating corporate-level BI solutions. Led by three BI experts, you’ll learn how to build, deploy, and query a BISM tabular model with step-by-step guides, examples, and best practices. This hands-on book shows you how the tabular model’s in-memory database enables you to perform rapid analytics—whether you’re a professional BI developer new to Analysis Services or familiar with its multidimensional model....

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  • Tham khảo sách 'modelling of mechanical systems structural elements francois axisa', kỹ thuật - công nghệ, cơ khí - chế tạo máy phục vụ nhu cầu học tập, nghiên cứu và làm việc hiệu quả

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  • This book presents and develops major numerical methods currently used for solving problems arising in quantitative finance. Our presentation splits into two parts. Part I is methodological, and offers a comprehensive toolkit on numerical methods and algorithms. This includes Monte Carlo simulation, numerical schemes for partial differential equations, stochastic optimization in discrete time, copula functions, transform-based methods and quadrature techniques. Part II is practical, and features a number of self-contained cases.

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  • In practice, however, earthquakes generate stronger ground motion than Level 1 but not exceeding Level 2 can occur in service life of a structure. In current seismic design, consideration was not given directly to changes in activities and risks to the seismic motion through time and the importance of adopting effective methods of repair and reinforcement. These factors can not be implemented fully into account by simply checking the elastic limit or reparability limits or structural collapse of a Level 1 or 2 earthquake motion forces based on current seismic design....

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  • The final chapter of the book presents an innovative method for fluid mechanical design in which an object within the flow field is build element-by-element. Each element is introduced into the flow, and its effect on a cost function is minimized with respect to the object’s position. An element may represent added material or a removed part of the existing structure. This chapter presents a strong degree of mathematical formality.

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  • Modeling Hydrologic Change: Statistical Methods is about modeling systems where change has affected data that will be used to calibrate and test models of the systems and where models will be used to forecast system responses after change occurs. The focus is not on the hydrology. Instead, hydrology serves as the discipline from which the applications are drawn to illustrate the principles of modeling and the detection of change. All four elements of the modeling process are discussed: conceptualization, formulation, calibration, and verification.

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  • Regression models form the core of the discipline of econometrics. Although econometricians routinely estimate a wide variety of statistical models, using many different types of data, the vast majority of these are either regression models or close relatives of them. In this chapter, we introduce the concept of a regression model, discuss several varieties of them, and introduce the estimation method that is most commonly used with regression models, namely, least squares.

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  • There is a bustling atmosphere in the headquarters of the globally active Confusio Corporation. Everything seems to be just fine. Yet, there is a bad atmosphere in the precious wood-paneled conference room of the managing director Paul Peppy. Peppy has drummed together his top managers from all important branch offices; a hard and uncompromising crackdown is urgently required! Concerning the topic of the crisis summit, he has intentionally left the participants in the dark.

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  • Chris Adcock is Professor of Financial Econometrics in the University of Sheffield. His career includes several years working in quantitative investment management in the City and, prior to that, a decade in management science consultancy. His research interests are in the development of robust and non-standard methods for modelling expected returns, portfolio selection methods and the properties of optimized portfolios. He has acted as an advisor to a number of asset management firms. He is the founding editor of the European Journal of Finance. George A.

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  • Robotics and computer vision are interdisciplinary subjects at the intersection of engineering and computer science. By their nature, they deal with both computers and the physical world. Although the former are in the latter, the workings of computers are best described in the black-and-white vocabulary of discrete mathematics, which is foreign to most classical models of reality, quantum physics notwithstanding. This class surveys some of the key tools of applied math to be used at the interface of continuous and discrete. It is not on robotics or computer vision.

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  • Tham khảo sách 'international macroeconomics and finance: theory and empirical methods', tài chính - ngân hàng, ngân hàng - tín dụng phục vụ nhu cầu học tập, nghiên cứu và làm việc hiệu quả

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  • One of the most important advancements in recent social science research (including applied social sciences and public policy) has been the application of quantitative or computational methods in studying the complex human or social systems. Research centers in computational social sciences have flourished on major university campuses. Among others, the University of Chicago, University of Washington, UCLA, and George Mason University have all established such a center recently to promote the multidisciplinary research related to social issues....

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