Georg Ch Pflug (119 results)

paperback. Condition: Good. Ex- library book with stamps/ stickers.

Condition: New. Series: Oberwolfach Seminars. Num Pages: 124 pages, biography. BIC Classification: PBT; PBWL. Category: (UP) Postgraduate, Research & Scholarly; (UU) Undergraduate. Dimension: 244 x 170 x 6. Weight in Grams: 217. . 1992. Paperback. . . . .

Condition: New. Series: Oberwolfach Seminars. Num Pages: 124 pages, biography. BIC Classification: PBT; PBWL. Category: (UP) Postgraduate, Research & Scholarly; (UU) Undergraduate. Dimension: 244 x 170 x 6. Weight in Grams: 217. . 1992. Paperback. . . . . Books ship from the US and Ireland.

Soft Cover. Condition: Good. Ex-library with the usual features. The interior is clean and tight. Binding is good. Cover shows light wear and has library label on the spine. 336 pages. Ex-Library.

Condition: As New. Unread book in perfect condition.

Condition: New.

Condition: New. In English.

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Gebundene Ausgabe. Condition: Wie neu. Gebraucht - Wie neu Ungelesenes, vollständiges Exemplar in sehr gutem Zustand. -Stochastic models are everywhere. In manufacturing, queuing models are used for modeling production processes, realistic inventory models are stochastic in nature. Stochastic models are considered in transportation and communication. Marketing models use stochastic descriptions of the demands and buyer's behaviors. In finance, market prices and exchange rates are assumed to be certain stochastic processes, and insurance claims appear at random times with random amounts. To each decision problem, a cost function is associated. Costs may be direct or indirect, like loss of time, quality deterioration, loss in production or dissatisfaction of customers. In decision making under uncertainty, the goal is to minimize the expected costs. However, in practically all realistic models, the calculation of the expected costs is impossible due to the model complexity. Simulation is the only practicable way of getting insight into such models. Thus, the problem of optimal decisions can be seen as getting simulation and optimization effectively combined. The field is quite new and yet the number of publications is enormous. This book does not even try to touch all work done in this area. Instead, many concepts are presented and treated with mathematical rigor and necessary conditions for the correctness of various approaches are stated. Optimization of Stochastic Models: The Interface Between Simulation and Optimization is suitable as a text for a graduate level course on Stochastic Models or as a secondary text for a graduate level course in Operations Research. 396 pp. Englisch.…

Condition: Gut. Zustand: Gut | Seiten: 348 | Sprache: Englisch | Produktart: Bücher | Uncertainties and changes are pervasive characteristics of modern systems involving interactions between humans, economics, nature and technology. These systems are often too complex to allow for precise evaluations and, as a result, the lack of proper management (control) may create significant risks. In order to develop robust strategies we need approaches which explic­ itly deal with uncertainties, risks and changing conditions. One rather general approach is to characterize (explicitly or implicitly) uncertainties by objec­ tive or subjective probabilities (measures of confidence or belief). This leads us to stochastic optimization problems which can rarely be solved by using the standard deterministic optimization and optimal control methods. In the stochastic optimization the accent is on problems with a large number of deci­ sion and random variables, and consequently the focus ofattention is directed to efficient solution procedures rather than to (analytical) closed-form solu­ tions. Objective and constraint functions of dynamic stochastic optimization problems have the form of multidimensional integrals of rather involved in­ that may have a nonsmooth and even discontinuous character - the tegrands typical situation for "hit-or-miss" type of decision making problems involving irreversibility ofdecisions or/and abrupt changes ofthe system. In general, the exact evaluation of such functions (as is assumed in the standard optimization and control theory) is practically impossible. Also, the problem does not often possess the separability properties that allow to derive the standard in control theory recursive (Bellman) equations.…

Condition: New. pp. 348.

Taschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - Uncertainties and changes are pervasive characteristics of modern systems involving interactions between humans, economics, nature and technology. These systems are often too complex to allow for precise evaluations and, as a result, the lack of proper management (control) may create significant risks. In order to develop robust strategies we need approaches which explic itly deal with uncertainties, risks and changing conditions. One rather general approach is to characterize (explicitly or implicitly) uncertainties by objec tive or subjective probabilities (measures of confidence or belief). This leads us to stochastic optimization problems which can rarely be solved by using the standard deterministic optimization and optimal control methods. In the stochastic optimization the accent is on problems with a large number of deci sion and random variables, and consequently the focus ofattention is directed to efficient solution procedures rather than to (analytical) closed-form solu tions. Objective and constraint functions of dynamic stochastic optimization problems have the form of multidimensional integrals of rather involved in that may have a nonsmooth and even discontinuous character - the tegrands typical situation for 'hit-or-miss' type of decision making problems involving irreversibility ofdecisions or/and abrupt changes ofthe system. In general, the exact evaluation of such functions (as is assumed in the standard optimization and control theory) is practically impossible. Also, the problem does not often possess the separability properties that allow to derive the standard in control theory recursive (Bellman) equations.…

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Condition: New. In English.

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Hardcover. Condition: Brand New. illustrated edition. 304 pages. 9.25x6.50x0.50 inches. In Stock.

Condition: New. In English.

Condition: New. In English.

Taschenbuch. Condition: Neu. Multistage Stochastic Optimization | Georg Ch. Pflug (u. a.) | Taschenbuch | Springer Series in Operations Research and Financial Engineering | xiv | Englisch | 2016 | Springer | EAN 9783319382678 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu. …

Taschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - The interaction of various ideas from different researchers provides a main impetus to mathematical prosress. An important way to make communication possible is through international conferences on more or less spezialized topics~ The existence of several centers for research in probabil ity and statistics in the eastern part of central Europe - somewhat vaguely described as the Pannonian area - led to the idea of organizing Pannonian Symposia on Mathematical Statistics (PS~1S). The second such symposium was held at Bad Tatzmannsdorf, Burgenland (Austria), from 14 to 20 June 1981. About 100 researchers from 13 countries participated in that event and about 70 papers were delivered. Most of the papers dealt with one of the following topics: nonparametric estimation theory, asymptotic theory of estimation, invariance principles, limit theorems and aoplications. Full versions of selected papers, all presenting new results are included in this volume. The editors take this opportunity to thank the following institutions for their assistance in making the conference possible: the Provincial Government of Burgenland, the Austrian Ministry for Research and Science, the Burgenland Chamber of Commerce, the Control Data Corporation, the Austrian Society for Statistics and Informatics, the Landes hypothekenbank Burgenland, the Volksbank Oberwart, and the Community and Kurbad AG of Bad Tatzmannsdorf. We are also greatly indebted to all those persons who helped in editing this volume and in particular to the vii W. Grossmann et al. reds.), Probability and Statistical Inference, vii-viii.…

Buch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - Discrete Approximation of Markovprocesses by Markovchains.- An Autoregressive Representation of ARMA Processes.- Characterization of a Type Multivariate Exponential Distributions.- Multivariate Time Series Analysis and Forecast.- Testing Approximate Validity of Hardy-Weinberg Law in Population Genetics.- On an Optimization Problem Related to Statistical Investigations.- A Construction of Extremal Processes.- Monte Carlo Investigation of Robust Methods.- Monte Carlo Methods for Solving Hyperbolic Equations.- The Compounding of the Binomial and Generalized Beta Distributions.- Empirical Bayes Estimation of Probability Density Function with Dirichlet Process Prior.- On the Asymptotic Properties of Minimum Contrast Estimates.- Contiguity in Some Nonregular Cases and its Applications.- The Notion of Asymptotically Least Favorable Configuration in Selection and Ranking Problems.- One Method of Stable Estimation of a Location Parameter.- Stochastic Integral Representation of Functionals from a Sequence of Martingales.- Comparison of Multisample Tests of Normality.- Almost Everywhere Convergence of Recursive Kernel Regression Function Estimates.- Estimation of a Multivariate Density by Orthogonal Series.- Longest Runs in Markov Chains.- Approximation and Smoothing of Surfaces in (P+1)-Dimensional Spaces.- The Comparison of Two-Unit Standby Redundant System with Two and Three States of Units.- A Probability Inequality of General Nature for the Maximum of Partial Sums.- Parametric Deviations in Linear Models.- Statistical Tests for Tausworthe Pseudo-Random Numbers.- Polynomials of Parameters in the Regression Model - Estimation and Design.- The Limiting Log-Likelihood Process for Discontinuous Multiparameter Density Families.- Two Kinds of Pooling Information in Cross-SectionalRegression Model.- Rate of Convergence for Simple Estimate in the Rejective Sampling.- Minimal Metrics in the Random Variables Space.- Robust Alternatives to the F-Fest for the Linear Model.- Orthogonal Series Estimates of a Regression Function with Applications in System Identification.- Generating Student's T Variates by a Modified Rejection Method.- Block Transmissibility and Quantization.- Invariantly Optimal Curve Estimators with Respect to Integrated Mean Error Risk.…

Condition: Gut. Zustand: Gut | Seiten: 402 | Sprache: Englisch | Produktart: Bücher | The interaction of various ideas from different researchers provides a main impetus to mathematical prosress. An important way to make communication possible is through international conferences on more or less spezialized topics~ The existence of several centers for research in probabil ity and statistics in the eastern part of central Europe - somewhat vaguely described as the Pannonian area - led to the idea of organizing Pannonian Symposia on Mathematical Statistics (PS~1S). The second such symposium was held at Bad Tatzmannsdorf, Burgenland (Austria), from 14 to 20 June 1981. About 100 researchers from 13 countries participated in that event and about 70 papers were delivered. Most of the papers dealt with one of the following topics: nonparametric estimation theory, asymptotic theory of estimation, invariance principles, limit theorems and aoplications. Full versions of selected papers, all presenting new results are included in this volume. The editors take this opportunity to thank the following institutions for their assistance in making the conference possible: the Provincial Government of Burgenland, the Austrian Ministry for Research and Science, the Burgenland Chamber of Commerce, the Control Data Corporation, the Austrian Society for Statistics and Informatics, the Landes­ hypothekenbank Burgenland, the Volksbank Oberwart, and the Community and Kurbad AG of Bad Tatzmannsdorf. We are also greatly indebted to all those persons who helped in editing this volume and in particular to the vii W. Grossmann et al. reds.), Probability and Statistical Inference, vii-viii.…

Condition: New. pp. 301.

Condition: New. pp. 274.