Towards Hybrid and Adaptive Computing, Anupam Shukla; Ritu Tiwari; Rahul Kala

Автор: Cameron
Название: Microeconometrics Using Stata
ISBN: 1597180734 ISBN-13(EAN): 9781597180733
Издательство: Taylor&Francis
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Цена: 83690.00 T
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Описание: Updated to reflect Stata 11, this revised edition offers a complete and up-to-date survey of microeconometric methods available in Stata. The authors employ the new margins command, emphasizing both marginal effects at the means and average marginal effects. They also replace the xi command with factor variables, which allow you to specify indicator variables and interaction effects. Along with several new examples, this edition presents the new gmm command for generalized method of moments and nonlinear instrumental-variables estimation. In addition, the chapter on maximum likelihood estimation incorporates enhancements made to ml in Stata 11.

Автор: Bartlomiej Beliczynski; Andrzej Dzielinski; Marcin
Название: Adaptive and Natural Computing Algorithms
ISBN: 3540715908 ISBN-13(EAN): 9783540715900
Издательство: Springer
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Цена: 121110.00 T
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Описание: The two volume set LNCS 4431 and LNCS 4432 constitutes the refereed proceedings of the 8th International Conference on Adaptive and Natural Computing Algorithms, ICANNGA 2007, held in Warsaw, Poland, in April 2007. The 178 revised full papers presented were carefully reviewed and selected from a total of 474 submissions.

Автор: Becketti
Название: Introduction to Time Series Using Stata
ISBN: 1597181323 ISBN-13(EAN): 9781597181327
Издательство: Taylor&Francis
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Цена: 75530.00 T
Наличие на складе: Невозможна поставка.
Описание: Recent decades have witnessed explosive growth in new and powerful tools for timeseries analysis. These innovations have overturned older approaches to forecasting, macroeconomic policy analysis, the study of productivity and long-run economic growth, and the trading of financial assets. Familiarity with these new tools on time series is an essential skill for statisticians, econometricians, and applied researchers. Introduction to Time Series Using Stata provides a step-by-step guide to essential timeseries techniques—from the incredibly simple to the quite complex—and, at the same time, demonstrates how these techniques can be applied in the Stata statistical package. The emphasis is on an understanding of the intuition underlying theoretical innovations and an ability to apply them. Real-world examples illustrate the application of each concept as it is introduced, and care is taken to highlight the pitfalls, as well as the power, of each new tool. Sean Becketti is a financial industry veteran with three decades of experience in academics, government, and private industry. Over the last two decades, Becketti has led proprietary research teams at several leading financial firms, responsible for the models underlying the valuation, hedging, and relative value analysis of some of the largest fixed-income portfolios in the world.

Автор: Kohler
Название: Data Analysis Using Stata, Third Edition
ISBN: 1597181102 ISBN-13(EAN): 9781597181105
Издательство: Taylor&Francis
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Цена: 74510.00 T
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Описание:

Data Analysis Using Stata, Third Edition is a comprehensive introduction to both statistical methods and Stata. Beginners will learn the logic of data analysis and interpretation and easily become self-sufficient data analysts. Readers already familiar with Stata will find it an enjoyable resource for picking up new tips and tricks.

The book is written as a self-study tutorial and organized around examples. It interactively introduces statistical techniques such as data exploration, description, and regression techniques for continuous and binary dependent variables. Step by step, readers move through the entire process of data analysis and in doing so learn the principles of Stata, data manipulation, graphical representation, and programs to automate repetitive tasks. This third edition includes advanced topics, such as factor-variables notation, average marginal effects, standard errors in complex survey, and multiple imputation in a way, that beginners of both data analysis and Stata can understand.

Using data from a longitudinal study of private households, the authors provide examples from the social sciences that are relatable to researchers from all disciplines. The examples emphasize good statistical practice and reproducible research. Readers are encouraged to download the companion package of datasets to replicate the examples as they work through the book. Each chapter ends with exercises to consolidate acquired skills.

Автор: Ville Kolehmainen; Pekka Toivanen; Bartlomiej Beli
Название: Adaptive and Natural Computing Algorithms
ISBN: 3642049206 ISBN-13(EAN): 9783642049200
Издательство: Springer
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Цена: 111790.00 T
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Описание: The ICANNGA series of conferences has been organized since 1993 and has a long history of promoting the principles and understanding of computational intelligence paradigms within the scienti?c community. Originally ICANNGA stood for "International Conference on Arti?cial Neural Networks and Genetic Algorithms," but in 2005 the conference was renamed to "International C- ference on Adaptive and Natural Computing Algorithms," while keeping the acronymICANNGA.The?rstICANNGAconferencewasheldinInnsbruckA- tria (1993), then Al es in France (1995), Norwich in the UK (1997), Portoroz in Slovenia (1999), Prague in the Czech Republic (2001), Roanne in France (2003), CoimbrainPortugal(2005)andWarsawinPoland(2007).ContinuingthisEu- peantradition, the9thICANNGA washeldinKuopio, Finland(2009).Thevast majority of ICANNGA conferences is organized by and based at a university. Drawing on the experience of previous events and following the same g- eral model, ICANNGA 2009 combined plenary lectures and technical sessions. Apart from being a widely recognized conference, it enhanced the possibility to exchange opinions through lectures and discussions, provided a great oppor- nity to meet new colleagues, as well as to renew old friendships and to facilitate the possibilities for international collaborations. As previously, the conference proceedings are published in the Springer LNCS series.

Автор: Bartlomiej Beliczynski; Andrzej Dzielinski; Marcin
Название: Adaptive and Natural Computing Algorithms
ISBN: 3540715894 ISBN-13(EAN): 9783540715894
Издательство: Springer
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Цена: 121110.00 T
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Описание: Constitutes the refereed proceedings of the 8th International Conference on Adaptive and Natural Computing Algorithms, ICANNGA 2007, held in Warsaw, Poland, in April 2007. This two volume set covers evolutionary computation, genetic algorithms, and particle swarm optimization. It also covers neural networks, and support vector machines.