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Stochastic Modelling and Control

Posted By: AvaxGenius
Stochastic Modelling and Control

Stochastic Modelling and Control by M. H. A. Davis , R. B. Vinter
English | PDF | 1985 | 405 Pages | ISBN : 9401086400 | 24.6 MB

This book aims to provide a unified treatment of input/output modelling and of control for discrete-time dynamical systems subject to random disturbances. The results presented are of wide applica­ bility in control engineering, operations research, econometric modelling and many other areas. There are two distinct approaches to mathematical modelling of physical systems: a direct analysis of the physical mechanisms that comprise the process, or a 'black box' approach based on analysis of input/output data.

Linear Algebra for the Sciences

Posted By: AvaxGenius
Linear Algebra for the Sciences

Linear Algebra for the Sciences by Manuel Benz , Thomas Kappeler
English | PDF EPUB (True) | 2023 | 268 Pages | ISBN : 3031272196 | 25.2 MB

This book is based on a course for first-semester science students, held by the second author at the University of Zurich several times. Its goal is threefold: to have students learn a minimal working knowledge of linear algebra, acquire some computational skills, and familiarize them with mathematical language to make mathematical literature more accessible. Therefore, we give precise definitions, introduce helpful notations, and state any results carefully worded. We provide no proofs of these results but typically illustrate them with numerous examples. Additionally, for better understanding, we often give supporting arguments for why they are valid.

Statistics and Data Analysis for Financial Engineering: with R examples, Second Edition

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Statistics and Data Analysis for Financial Engineering: with R examples, Second Edition

Statistics and Data Analysis for Financial Engineering: with R examples, Second Edition by David Ruppert
English | PDF | 2015 | 736 Pages | ISBN : 1493926136 | 13.2 MB

The new edition of this influential textbook, geared towards graduate or advanced undergraduate students, teaches the statistics necessary for financial engineering. In doing so, it illustrates concepts using financial markets and economic data, R Labs with real-data exercises, and graphical and analytic methods for modeling and diagnosing modeling errors. These methods are critical because financial engineers now have access to enormous quantities of data.