Welcome to our book review site go-pdf.online!
You may have to Search all our reviewed books and magazines, click the sign up button below to create a free account.
Financial Statistics and Mathematical Finance
Mathematical finance has grown into a huge area of research which requires a lot of care and a large number of sophisticated mathematical tools. Mathematically rigorous and yet accessible to advanced level practitioners and mathematicians alike, it considers various aspects of the application of statistical methods in finance and illustrates some of the many ways that statistical tools are used in financial applications. Financial Statistics and Mathematical Finance: Provides an introduction to the basics of financial statistics and mathematical finance. Explains the use and importance of statistical methods in econometrics and financial engineering. Illustrates the importance of derivatives...
Artificial Intelligence, Big Data and Data Science in Statistics
This book discusses the interplay between statistics, data science, machine learning and artificial intelligence, with a focus on environmental science, the natural sciences, and technology. It covers the state of the art from both a theoretical and a practical viewpoint and describes how to successfully apply machine learning methods, demonstrating the benefits of statistics for modeling and analyzing high-dimensional and big data. The book’s expert contributions include theoretical studies of machine learning methods, expositions of general methodologies for sound statistical analyses of data as well as novel approaches to modeling and analyzing data for specific problems and areas. In terms of applications, the contributions deal with data as arising in industrial quality control, autonomous driving, transportation and traffic, chip manufacturing, photovoltaics, football, transmission of infectious diseases, Covid-19 and public health. The book will appeal to statisticians and data scientists, as well as engineers and computer scientists working in related fields or applications.
Stochastic Models, Statistics and Their Applications
This volume presents selected and peer-reviewed contributions from the 14th Workshop on Stochastic Models, Statistics and Their Applications, held in Dresden, Germany, on March 6-8, 2019. Addressing the needs of theoretical and applied researchers alike, the contributions provide an overview of the latest advances and trends in the areas of mathematical statistics and applied probability, and their applications to high-dimensional statistics, econometrics and time series analysis, statistics for stochastic processes, statistical machine learning, big data and data science, random matrix theory, quality control, change-point analysis and detection, finance, copulas, survival analysis and reliability, sequential experiments, empirical processes, and microsimulations. As the book demonstrates, stochastic models and related statistical procedures and algorithms are essential to more comprehensively understanding and solving present-day problems arising in e.g. the natural sciences, machine learning, data science, engineering, image analysis, genetics, econometrics and finance.
Stochastic Models, Statistics and Their Applications
This volume presents the latest advances and trends in stochastic models and related statistical procedures. Selected peer-reviewed contributions focus on statistical inference, quality control, change-point analysis and detection, empirical processes, time series analysis, survival analysis and reliability, statistics for stochastic processes, big data in technology and the sciences, statistical genetics, experiment design, and stochastic models in engineering. Stochastic models and related statistical procedures play an important part in furthering our understanding of the challenging problems currently arising in areas of application such as the natural sciences, information technology, engineering, image analysis, genetics, energy and finance, to name but a few. This collection arises from the 12th Workshop on Stochastic Models, Statistics and Their Applications, Wroclaw, Poland.
Operations Research Proceedings 2001
This volume contains the proceedings of the 200 I International Conference on Operations Research (OR 2(01) held at the Gerhard-Mercator-University Duisburg, September 3-5,2001. OR 200 1 was organized under the auspices of the German Society of Operations Research, Gesellschaft für Operations Research (GOR e. V.). The conference and the annual general meeting were attended by 360 participants from 20 countries. The presentation of 220 papers was organized in 15 sections. According to Duisburg as hosting city for this event OR 200 1 emphasized on contributions of OR in the areas of energy, transport and traftk. The program consisted of2 plenary lectures (Reinhard Selten and Jörg Hennerkes) ...
Frontiers in Statistical Quality Control 11
The main focus of this edited volume is on three major areas of statistical quality control: statistical process control (SPC), acceptance sampling and design of experiments. The majority of the papers deal with statistical process control, while acceptance sampling and design of experiments are also treated to a lesser extent. The book is organized into four thematic parts, with Part I addressing statistical process control. Part II is devoted to acceptance sampling. Part III covers the design of experiments, while Part IV discusses related fields. The twenty-three papers in this volume stem from The 11th International Workshop on Intelligent Statistical Quality Control, which was held in Sydney, Australia from August 20 to August 23, 2013. The event was hosted by Professor Ross Sparks, CSIRO Mathematics, Informatics and Statistics, North Ryde, Australia and was jointly organized by Professors S. Knoth, W. Schmid and Ross Sparks. The papers presented here were carefully selected and reviewed by the scientific program committee, before being revised and adapted for this volume.
Frontiers in Statistical Quality Control 10
The 10th International Workshop on Intelligent Statistical Quality Control took place in Seattle, USA, Aug 18-20, 2010. It was hosted by Professor C. M. Mastrangelo, Department of Industrial and Systems Engineering, University of Washington, Seattle. The workshop was jointly organized by Professors H. J. Lenz, C. M. Mastrangelo, W. Schmid and P.T. Wilrich. The twenty-seven papers in this volume were carefully selected by the scientific program committee, reviewed by its members, revised by the authors and, finally, adapted for this volume by the editors. The book is divided into two parts: Part I "On-line Control" covers fields like control charting, monitoring and surveillance as well as acceptance sampling. Part II "Off-line Control" is devoted to experimental design, process capability analysis and data quality. The purpose of the book is on the one hand to provide insights into important new developments in the area of statistical quality control – especially surveillance and monitoring – and on the other hand to critically discuss methods used in on-line and off-line statistical quality control.
Stochastic Models, Statistics and Their Applications
This volume presents selected and peer-reviewed contributions from the 14th Workshop on Stochastic Models, Statistics and Their Applications, held in Dresden, Germany, on March 6-8, 2019. Addressing the needs of theoretical and applied researchers alike, the contributions provide an overview of the latest advances and trends in the areas of mathematical statistics and applied probability, and their applications to high-dimensional statistics, econometrics and time series analysis, statistics for stochastic processes, statistical machine learning, big data and data science, random matrix theory, quality control, change-point analysis and detection, finance, copulas, survival analysis and reliability, sequential experiments, empirical processes, and microsimulations. As the book demonstrates, stochastic models and related statistical procedures and algorithms are essential to more comprehensively understanding and solving present-day problems arising in e.g. the natural sciences, machine learning, data science, engineering, image analysis, genetics, econometrics and finance.
Basiswissen Statistik
In diesem Buch werden in kompakter Form mithilfe zahlreicher Beispiele die üblichen Modelle und Methoden der angewandten Wahrscheinlichkeitstheorie und Statistik dargestellt. Es ist daher insbesondere für angehende Wirtschaftswissenschaftler, Ingenieure und Informatiker geeignet, welchen auch das didaktische Konzept des Buchs entgegenkommt: Verständnisfragen und Aufgaben in Form von „Meilensteinen“ erleichtern das eigenständige Überprüfen des Lernfortschritts. Ein ausführlicher mathematischer Anhang „Mathematik kompakt“ stellt die wichtigsten Ergebnisse aus Analysis und linearer Algebra zum effizienten Nachschlagen zur Verfügung. Ein Glossar mit den wichtigsten englischen Begriffen sowie Tabellen der statistischen Testverteilungen runden die Darstellung ab.
Modelling and Development of Intelligent Systems
This book constitutes the refereed proceedings of the 8th International Conference on Modelling and Development of Intelligent Systems, MDIS 2022, held in Sibiu, Romania, during October 28–30, 2022. The 21 papers included in this book were carefully reviewed and selected from 48 submissions. They were organized in the following topical sections as follows: intelligent systems for decision support; machine learning; mathematical models for development of intelligent systems; and modelling and optimization of dynamic systems.
