Описание: The concept of "reformulation" has long been playing an important role in mathematical programming. A classical example is the penalization technique in constrained optimization that transforms the constraints into the objective function via a penalty function thereby reformulating a constrained problem as an equivalent or approximately equivalent unconstrained problem. More recent trends consist of the reformulation of various mathematical programming prob- lems, including variational inequalities and complementarity problems, into equivalent systems of possibly nonsmooth, piecewise smooth or semismooth nonlinear equations, or equivalent unconstrained optimization problems that are usually differentiable, but in general not twice differentiable. Because of the recent advent of various tools in nonsmooth analysis, the reformulation approach has become increasingly profound and diversified. In view of growing interests in this active field, we planned to organize a cluster of sessions entitled "Reformulation - Nonsmooth, Piecewise Smooth, Semismooth and Smoothing Methods" in the 16th International Symposium on Mathematical Programming (ismp97) held at Lausanne EPFL, Switzerland on August 24-29, 1997. Responding to our invitation, thirty-eight people agreed to give a talk within the cluster, which enabled us to organize thirteen sessions in total. We think that it was one of the largest and most exciting clusters in the symposium. Thanks to the earnest support by the speakers and the chairpersons, the sessions attracted much attention of the participants and were filled with great enthusiasm of the audience.
Описание: Collects papers that cover such areas as linear and nonlinear complementarity problems, variational inequality problems, nonsmooth equations and nonsmooth optimization problems, economic and network equilibrium problems, semidefinite programming problems, maximal monotone operator problems, and mathematical programs with equilibrium constraints.
Автор: Hyndman Название: Forecasting with Exponential Smoothing ISBN: 3540719164 ISBN-13(EAN): 9783540719168 Издательство: Springer Рейтинг: Цена: 13974.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: However, a modeling framework incorporating stochastic models, likelihood calculation, prediction intervals and procedures for model selection, was not developed until recently. More advanced topics are covered in Part 3, including the mathematical properties of the models and extensions of the models for specific problems.
Автор: Jeffrey Hart Название: Nonparametric Smoothing and Lack-of-Fit Tests ISBN: 1475727240 ISBN-13(EAN): 9781475727241 Издательство: Springer Рейтинг: Цена: 13974.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: An exploration of the use of smoothing methods in testing the fit of parametric regression models.
Автор: Wolfgang H?rdle Название: Smoothing Techniques ISBN: 1461287685 ISBN-13(EAN): 9781461287681 Издательство: Springer Рейтинг: Цена: 19564.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: A principal feature of smoothing, the averaging of data points in a prescribed neighborhood, is not really practicable in dimensions greater than three if we have just one hundred data points.
Автор: Jeffrey S. Simonoff Название: Smoothing Methods in Statistics ISBN: 1461284724 ISBN-13(EAN): 9781461284727 Издательство: Springer Рейтинг: Цена: 23058.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Focussing on applications, this book covers a very broad range, including simple and complex univariate and multivariate density estimation, nonparametric regression estimation, categorical data smoothing, and applications of smoothing to other areas of statistics.
Автор: Howard L. Weinert Название: Fixed Interval Smoothing for State Space Models ISBN: 0792372999 ISBN-13(EAN): 9780792372998 Издательство: Springer Рейтинг: Цена: 21655.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Fixed-interval smoothing is a method of extracting information from inaccurate data. This monograph addresses problems for which a linear stochastic state space model is available, in which case the objective is to compute the linear least-squares estimate of the state vector in a fixed interval, using observations collected in that interval.
Автор: Chong Gu Название: Smoothing Spline ANOVA Models ISBN: 1461453682 ISBN-13(EAN): 9781461453680 Издательство: Springer Рейтинг: Цена: 20962.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Updated to include the latest computational methods, this second edition explains how to use the `gss` R package and features expanded empirical studies, a reorganized content, and a further new appendix analyzing new and controversial topics in smoothing.
Автор: Chong Gu Название: Smoothing Spline ANOVA Models ISBN: 1489989846 ISBN-13(EAN): 9781489989840 Издательство: Springer Рейтинг: Цена: 18167.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Updated to include the latest computational methods, this second edition explains how to use the `gss` R package and features expanded empirical studies, a reorganized content, and a further new appendix analyzing new and controversial topics in smoothing.
Автор: Chacon Название: Multivariate Kernel Smoothing And I ISBN: 1498763014 ISBN-13(EAN): 9781498763011 Издательство: Taylor&Francis Рейтинг: Цена: 13779.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Kernel smoothing has greatly evolved since its inception to become an essential methodology in the Data Science tool kit for the 21st century. Its widespread adoption is due to its fundamental role for multivariate exploratory data analysis, as well as the crucial role it plays in composite solutions to complex data challenges.
Автор: Horova Ivanka Et Al Название: Kernel Smoothing In Matlab: Theory And Practice Of Kernel Smoothing ISBN: 9814405485 ISBN-13(EAN): 9789814405485 Издательство: World Scientific Publishing Рейтинг: Цена: 12830.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Offers a comprehensive overview of statistical theory and emphases the implementation of presented methods in Matlab. This title contains various Matlab scripts useful for kernel smoothing of density, cumulative distribution function, regression function, hazard function, indices of quality and bivariate density.
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