Multivariate Statistical Modeling In Engineering And Management

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Multivariate Statistical Modeling In Engineering And Management

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Author : Jhareswar Maiti
language : en
Publisher: CRC Press
Release Date : 2022-10-25

Multivariate Statistical Modeling In Engineering And Management written by Jhareswar Maiti and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-10-25 with Mathematics categories.

The book focuses on problem solving for practitioners and model building for academicians under multivariate situations. This book helps readers in understanding the issues, such as knowing variability, extracting patterns, building relationships, and making objective decisions. A large number of multivariate statistical models are covered in the book. The readers will learn how a practical problem can be converted to a statistical problem and how the statistical solution can be interpreted as a practical solution. Key features: Links data generation process with statistical distributions in multivariate domain Provides step by step procedure for estimating parameters of developed models Provides blueprint for data driven decision making Includes practical examples and case studies relevant for intended audiences The book will help everyone involved in data driven problem solving, modeling and decision making.

Proceedings Of The Seventh International Conference On Management Science And Engineering Management

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Author : Jiuping Xu
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-09-20

Proceedings Of The Seventh International Conference On Management Science And Engineering Management written by Jiuping Xu and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-09-20 with Business & Economics categories.

This book presents the proceedings of the Seventh International Conference on Management Science and Engineering Management (ICMSEM2013) held from November 7 to 9, 2013 at Drexel University, Philadelphia, Pennsylvania, USA and organized by the International Society of Management Science and Engineering Management, Sichuan University (Chengdu, China) and Drexel University (Philadelphia, Pennsylvania, USA). The goals of the Conference are to foster international research collaborations in Management Science and Engineering Management as well as to provide a forum to present current research findings. The selected papers cover various areas in management science and engineering management, such as Decision Support Systems, Multi-Objective Decisions, Uncertain Decisions, Computational Mathematics, Information Systems, Logistics and Supply Chain Management, Relationship Management, Scheduling and Control, Data Warehousing and Data Mining, Electronic Commerce, Neural Networks, Stochastic Models and Simulation, Fuzzy Programming, Heuristics Algorithms, Risk Control, Organizational Behavior, Green Supply Chains, and Carbon Credits. The proceedings introduce readers to novel ideas on and different problem-solving methods in Management Science and Engineering Management. We selected excellent papers from all over the world, integrating their expertise and ideas in order to improve research on Management Science and Engineering Management.

Innovations In Multivariate Statistical Modeling

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Author : Andriëtte Bekker
language : en
Publisher: Springer Nature
Release Date : 2022-12-15

Innovations In Multivariate Statistical Modeling written by Andriëtte Bekker and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-12-15 with Mathematics categories.

Multivariate statistical analysis has undergone a rich and varied evolution during the latter half of the 20th century. Academics and practitioners have produced much literature with diverse interests and with varying multidisciplinary knowledge on different topics within the multivariate domain. Due to multivariate algebra being of sustained interest and being a continuously developing field, its appeal breaches laterally across multiple disciplines to act as a catalyst for contemporary advances, with its core inferential genesis remaining in that of statistics. It is exactly this varied evolution caused by an influx in data production, diffusion, and understanding in scientific fields that has blurred many lines between disciplines. The cross-pollination between statistics and biology, engineering, medical science, computer science, and even art, has accelerated the vast amount of questions that statistical methodology has to answer and report on. These questions are often multivariate in nature, hoping to elucidate uncertainty on more than one aspect at the same time, and it is here where statistical thinking merges mathematical design with real life interpretation for understanding this uncertainty. Statistical advances benefit from these algebraic inventions and expansions in the multivariate paradigm. This contributed volume aims to usher novel research emanating from a multivariate statistical foundation into the spotlight, with particular significance in multidisciplinary settings. The overarching spirit of this volume is to highlight current trends, stimulate a focus on, and connect multidisciplinary dots from and within multivariate statistical analysis. Guided by these thoughts, a collection of research at the forefront of multivariate statistical thinking is presented here which has been authored by globally recognized subject matter experts.

Graduate Announcement

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Author : University of Michigan--Dearborn
language : en
Publisher:
Release Date : 1998

Graduate Announcement written by University of Michigan--Dearborn and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1998 with categories.

Bayesian Model Selection And Statistical Modeling

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Author : Tomohiro Ando
language : en
Publisher: CRC Press
Release Date : 2010-05-27

Bayesian Model Selection And Statistical Modeling written by Tomohiro Ando and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-05-27 with Mathematics categories.

Along with many practical applications, Bayesian Model Selection and Statistical Modeling presents an array of Bayesian inference and model selection procedures. It thoroughly explains the concepts, illustrates the derivations of various Bayesian model selection criteria through examples, and provides R code for implementation. The author shows how to implement a variety of Bayesian inference using R and sampling methods, such as Markov chain Monte Carlo. He covers the different types of simulation-based Bayesian model selection criteria, including the numerical calculation of Bayes factors, the Bayesian predictive information criterion, and the deviance information criterion. He also provides a theoretical basis for the analysis of these criteria. In addition, the author discusses how Bayesian model averaging can simultaneously treat both model and parameter uncertainties. Selecting and constructing the appropriate statistical model significantly affect the quality of results in decision making, forecasting, stochastic structure explorations, and other problems. Helping you choose the right Bayesian model, this book focuses on the framework for Bayesian model selection and includes practical examples of model selection criteria.

Bayesian Statistical Modelling

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Author : Peter Congdon
language : en
Publisher: John Wiley & Sons
Release Date : 2007-04-04

Bayesian Statistical Modelling written by Peter Congdon and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007-04-04 with Mathematics categories.

Bayesian methods combine the evidence from the data at hand with previous quantitative knowledge to analyse practical problems in a wide range of areas. The calculations were previously complex, but it is now possible to routinely apply Bayesian methods due to advances in computing technology and the use of new sampling methods for estimating parameters. Such developments together with the availability of freeware such as WINBUGS and R have facilitated a rapid growth in the use of Bayesian methods, allowing their application in many scientific disciplines, including applied statistics, public health research, medical science, the social sciences and economics. Following the success of the first edition, this reworked and updated book provides an accessible approach to Bayesian computing and analysis, with an emphasis on the principles of prior selection, identification and the interpretation of real data sets. The second edition: Provides an integrated presentation of theory, examples, applications and computer algorithms. Discusses the role of Markov Chain Monte Carlo methods in computing and estimation. Includes a wide range of interdisciplinary applications, and a large selection of worked examples from the health and social sciences. Features a comprehensive range of methodologies and modelling techniques, and examines model fitting in practice using Bayesian principles. Provides exercises designed to help reinforce the reader’s knowledge and a supplementary website containing data sets and relevant programs. Bayesian Statistical Modelling is ideal for researchers in applied statistics, medical science, public health and the social sciences, who will benefit greatly from the examples and applications featured. The book will also appeal to graduate students of applied statistics, data analysis and Bayesian methods, and will provide a great source of reference for both researchers and students. Praise for the First Edition: “It is a remarkable achievement to have carried out such a range of analysis on such a range of data sets. I found this book comprehensive and stimulating, and was thoroughly impressed with both the depth and the range of the discussions it contains.” – ISI - Short Book Reviews “This is an excellent introductory book on Bayesian modelling techniques and data analysis” – Biometrics “The book fills an important niche in the statistical literature and should be a very valuable resource for students and professionals who are utilizing Bayesian methods.” – Journal of Mathematical Psychology

Statistical Modeling Using Bayesian Latent Gaussian Models

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Author : Birgir Hrafnkelsson
language : en
Publisher: Springer Nature
Release Date : 2023-11-08

Statistical Modeling Using Bayesian Latent Gaussian Models written by Birgir Hrafnkelsson and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-11-08 with Mathematics categories.

This book focuses on the statistical modeling of geophysical and environmental data using Bayesian latent Gaussian models. The structure of these models is described in a thorough introductory chapter, which explains how to construct prior densities for the model parameters, how to infer the parameters using Bayesian computation, and how to use the models to make predictions. The remaining six chapters focus on the application of Bayesian latent Gaussian models to real examples in glaciology, hydrology, engineering seismology, seismology, meteorology and climatology. These examples include: spatial predictions of surface mass balance; the estimation of Antarctica’s contribution to sea-level rise; the estimation of rating curves for the projection of water level to discharge; ground motion models for strong motion; spatial modeling of earthquake magnitudes; weather forecasting based on numerical model forecasts; and extreme value analysis of precipitation on a high-dimensional grid. The book is aimed at graduate students and experts in statistics, geophysics, environmental sciences, engineering, and related fields.

Applied Statistical Modeling And Data Analytics

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Author : Srikanta Mishra
language : en
Publisher: Elsevier
Release Date : 2017-10-27

Applied Statistical Modeling And Data Analytics written by Srikanta Mishra and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-10-27 with Science categories.

Applied Statistical Modeling and Data Analytics: A Practical Guide for the Petroleum Geosciences provides a practical guide to many of the classical and modern statistical techniques that have become established for oil and gas professionals in recent years. It serves as a "how to" reference volume for the practicing petroleum engineer or geoscientist interested in applying statistical methods in formation evaluation, reservoir characterization, reservoir modeling and management, and uncertainty quantification. Beginning with a foundational discussion of exploratory data analysis, probability distributions and linear regression modeling, the book focuses on fundamentals and practical examples of such key topics as multivariate analysis, uncertainty quantification, data-driven modeling, and experimental design and response surface analysis. Data sets from the petroleum geosciences are extensively used to demonstrate the applicability of these techniques. The book will also be useful for professionals dealing with subsurface flow problems in hydrogeology, geologic carbon sequestration, and nuclear waste disposal. - Authored by internationally renowned experts in developing and applying statistical methods for oil & gas and other subsurface problem domains - Written by practitioners for practitioners - Presents an easy to follow narrative which progresses from simple concepts to more challenging ones - Includes online resources with software applications and practical examples for the most relevant and popular statistical methods, using data sets from the petroleum geosciences - Addresses the theory and practice of statistical modeling and data analytics from the perspective of petroleum geoscience applications

Daily Graphic

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Author : Ransford Tetteh
language : en
Publisher: Graphic Communications Group
Release Date : 2010-01-11

Daily Graphic written by Ransford Tetteh and has been published by Graphic Communications Group this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-01-11 with categories.

Road Traffic Modeling And Management

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Author : Fouzi Harrou
language : en
Publisher: Elsevier
Release Date : 2021-10-05

Road Traffic Modeling And Management written by Fouzi Harrou and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-10-05 with Transportation categories.

Road Traffic Modeling and Management: Using Statistical Monitoring and Deep Learning provides a framework for understanding and enhancing road traffic monitoring and management. The book examines commonly used traffic analysis methodologies as well the emerging methods that use deep learning methods. Other sections discuss how to understand statistical models and machine learning algorithms and how to apply them to traffic modeling, estimation, forecasting and traffic congestion monitoring. Providing both a theoretical framework along with practical technical solutions, this book is ideal for researchers and practitioners who want to improve the performance of intelligent transportation systems. - Provides integrated, up-to-date and complete coverage of the key components for intelligent transportation systems: traffic modeling, forecasting, estimation and monitoring - Uses methods based on video and time series data for traffic modeling and forecasting - Includes case studies, key processes guidance and comparisons of different methodologies