Advances In Mathematical And Statistical Modeling

Advances In Mathematical And Statistical Modeling Book in PDF, ePub and Kindle version is available to download in english. Read online anytime anywhere directly from your device. Click on the download button below to get a free pdf file of Advances In Mathematical And Statistical Modeling book. This book definitely worth reading, it is an incredibly well-written.

Advances in Mathematical and Statistical Modeling

Author : Barry C. Arnold,N. Balakrishnan,Jose-Maria Sarabia Alegria,Roberto Minguez
Publisher : Springer Science & Business Media
Page : 374 pages
File Size : 53,9 Mb
Release : 2009-04-09
Category : Mathematics
ISBN : 9780817646264

Get Book

Advances in Mathematical and Statistical Modeling by Barry C. Arnold,N. Balakrishnan,Jose-Maria Sarabia Alegria,Roberto Minguez Pdf

Enrique Castillo is a leading figure in several mathematical and engineering fields. Organized to honor Castillo’s significant contributions, this volume is an outgrowth of the "International Conference on Mathematical and Statistical Modeling," and covers recent advances in the field. Applications to safety, reliability and life-testing, financial modeling, quality control, general inference, as well as neural networks and computational techniques are presented.

Recent Advances in Mathematical and Statistical Methods

Author : D. Marc Kilgour,Herb Kunze,Roman Makarov,Roderick Melnik,Xu Wang
Publisher : Springer
Page : 646 pages
File Size : 52,8 Mb
Release : 2018-11-04
Category : Computers
ISBN : 9783319997193

Get Book

Recent Advances in Mathematical and Statistical Methods by D. Marc Kilgour,Herb Kunze,Roman Makarov,Roderick Melnik,Xu Wang Pdf

This book focuses on the recent development of methodologies and computation methods in mathematical and statistical modelling, computational science and applied mathematics. It emphasizes the development of theories and applications, and promotes interdisciplinary endeavour among mathematicians, statisticians, scientists, engineers and researchers from other disciplines. The book provides ideas, methods and tools in mathematical and statistical modelling that have been developed for a wide range of research fields, including medical, health sciences, biology, environmental science, engineering, physics and chemistry, finance, economics and social sciences. It presents original results addressing real-world problems. The contributions are products of a highly successful meeting held in August 2017 on the main campus of Wilfrid Laurier University, in Waterloo, Canada, the International Conference on Applied Mathematics, Modeling and Computational Science (AMMCS-2017). They make this book a valuable resource for readers interested not only in a broader overview of the methods, ideas and tools in mathematical and statistical approaches, but also in how they can attain valuable insights into problems arising in other disciplines.

Statistical Modeling and Computation

Author : Dirk P. Kroese,Joshua C.C. Chan
Publisher : Springer Science & Business Media
Page : 412 pages
File Size : 43,5 Mb
Release : 2013-11-18
Category : Computers
ISBN : 9781461487753

Get Book

Statistical Modeling and Computation by Dirk P. Kroese,Joshua C.C. Chan Pdf

This textbook on statistical modeling and statistical inference will assist advanced undergraduate and graduate students. Statistical Modeling and Computation provides a unique introduction to modern Statistics from both classical and Bayesian perspectives. It also offers an integrated treatment of Mathematical Statistics and modern statistical computation, emphasizing statistical modeling, computational techniques, and applications. Each of the three parts will cover topics essential to university courses. Part I covers the fundamentals of probability theory. In Part II, the authors introduce a wide variety of classical models that include, among others, linear regression and ANOVA models. In Part III, the authors address the statistical analysis and computation of various advanced models, such as generalized linear, state-space and Gaussian models. Particular attention is paid to fast Monte Carlo techniques for Bayesian inference on these models. Throughout the book the authors include a large number of illustrative examples and solved problems. The book also features a section with solutions, an appendix that serves as a MATLAB primer, and a mathematical supplement.​

Advances in Statistical Modeling and Inference

Author : Vijay Nair
Publisher : World Scientific
Page : 698 pages
File Size : 47,8 Mb
Release : 2007
Category : Mathematics
ISBN : 9789812708298

Get Book

Advances in Statistical Modeling and Inference by Vijay Nair Pdf

There have been major developments in the field of statistics over the last quarter century, spurred by the rapid advances in computing and data-measurement technologies. These developments have revolutionized the field and have greatly influenced research directions in theory and methodology. Increased computing power has spawned entirely new areas of research in computationally-intensive methods, allowing us to move away from narrowly applicable parametric techniques based on restrictive assumptions to much more flexible and realistic models and methods. These computational advances have also led to the extensive use of simulation and Monte Carlo techniques in statistical inference. All of these developments have, in turn, stimulated new research in theoretical statistics. This volume provides an up-to-date overview of recent advances in statistical modeling and inference. Written by renowned researchers from across the world, it discusses flexible models, semi-parametric methods and transformation models, nonparametric regression and mixture models, survival and reliability analysis, and re-sampling techniques. With its coverage of methodology and theory as well as applications, the book is an essential reference for researchers, graduate students, and practitioners.

Mathematical and Statistical Models and Methods in Reliability

Author : V.V. Rykov,N. Balakrishnan,M.S. Nikulin
Publisher : Springer Science & Business Media
Page : 465 pages
File Size : 43,7 Mb
Release : 2010-11-02
Category : Technology & Engineering
ISBN : 9780817649715

Get Book

Mathematical and Statistical Models and Methods in Reliability by V.V. Rykov,N. Balakrishnan,M.S. Nikulin Pdf

The book is a selection of invited chapters, all of which deal with various aspects of mathematical and statistical models and methods in reliability. Written by renowned experts in the field of reliability, the contributions cover a wide range of applications, reflecting recent developments in areas such as survival analysis, aging, lifetime data analysis, artificial intelligence, medicine, carcinogenesis studies, nuclear power, financial modeling, aircraft engineering, quality control, and transportation. Mathematical and Statistical Models and Methods in Reliability is an excellent reference text for researchers and practitioners in applied probability and statistics, industrial statistics, engineering, medicine, finance, transportation, the oil and gas industry, and artificial intelligence.

Statistical Modeling and Applications on Real-Time Problems

Author : Chandra Shekhar,Raghaw Raman Sinha
Publisher : CRC Press
Page : 249 pages
File Size : 51,5 Mb
Release : 2024-06-06
Category : Technology & Engineering
ISBN : 9781040031476

Get Book

Statistical Modeling and Applications on Real-Time Problems by Chandra Shekhar,Raghaw Raman Sinha Pdf

In an era dominated by mathematical and statistical models, this book unravels the profound significance of these tools in decoding uncertainties within numerical, observational, and calculation-based data. From governmental institutions to private entities, statistical prediction models provide a critical framework for optimal decision-making, offering nuanced insights into diverse realms, from climate to production and beyond. This book ·Serves as a comprehensive resource in statistical modeling, methodologies, and optimization techniques across various domains. ·Features contributions from global authors; the compilation comprises 10 insightful chapters, each addressing critical aspects of estimation and optimization through statistical modeling. ·Covers a spectrum of topics, from non-parametric goodness-of-fit statistics to Bayesian applications; the book explores novel resampling methods, advanced measures for empirical mode, and transient behavior analysis in queueing systems. ·Includes asymptotic properties of goodness-of-fit statistics, practical applications of Bayesian Statistics, modifications to the Hard EM algorithm, and explicit transient probabilities. ·Culminates with an exploration of an inventory model for perishable items, integrating preservation technology and learning effects to determine the economic order quantity. This book stands as a testament to global collaboration, offering a rich tapestry of commendable statistical and mathematical modeling alongside real-world problem-solving. It is poised to ignite further exploration, discussion, and innovation in the realms of statistical modeling and optimization.

Advances in Statistical Models for Data Analysis

Author : Isabella Morlini,Tommaso Minerva,Maurizio Vichi
Publisher : Springer
Page : 268 pages
File Size : 46,8 Mb
Release : 2015-09-04
Category : Mathematics
ISBN : 9783319173771

Get Book

Advances in Statistical Models for Data Analysis by Isabella Morlini,Tommaso Minerva,Maurizio Vichi Pdf

This edited volume focuses on recent research results in classification, multivariate statistics and machine learning and highlights advances in statistical models for data analysis. The volume provides both methodological developments and contributions to a wide range of application areas such as economics, marketing, education, social sciences and environment. The papers in this volume were first presented at the 9th biannual meeting of the Classification and Data Analysis Group (CLADAG) of the Italian Statistical Society, held in September 2013 at the University of Modena and Reggio Emilia, Italy.

Advances in Complex Data Modeling and Computational Methods in Statistics

Author : Anna Maria Paganoni,Piercesare Secchi
Publisher : Springer
Page : 210 pages
File Size : 55,9 Mb
Release : 2014-11-04
Category : Mathematics
ISBN : 9783319111490

Get Book

Advances in Complex Data Modeling and Computational Methods in Statistics by Anna Maria Paganoni,Piercesare Secchi Pdf

The book is addressed to statisticians working at the forefront of the statistical analysis of complex and high dimensional data and offers a wide variety of statistical models, computer intensive methods and applications: network inference from the analysis of high dimensional data; new developments for bootstrapping complex data; regression analysis for measuring the downsize reputational risk; statistical methods for research on the human genome dynamics; inference in non-euclidean settings and for shape data; Bayesian methods for reliability and the analysis of complex data; methodological issues in using administrative data for clinical and epidemiological research; regression models with differential regularization; geostatistical methods for mobility analysis through mobile phone data exploration. This volume is the result of a careful selection among the contributions presented at the conference "S.Co.2013: Complex data modeling and computationally intensive methods for estimation and prediction" held at the Politecnico di Milano, 2013. All the papers published here have been rigorously peer-reviewed.

Recent Developments in Mathematical, Statistical and Computational Sciences

Author : D. Marc Kilgour,Herb Kunze,Roman Makarov,Roderick Melnik,Xu Wang
Publisher : Springer
Page : 0 pages
File Size : 55,5 Mb
Release : 2022-08-31
Category : Mathematics
ISBN : 3030635937

Get Book

Recent Developments in Mathematical, Statistical and Computational Sciences by D. Marc Kilgour,Herb Kunze,Roman Makarov,Roderick Melnik,Xu Wang Pdf

This book constitutes an up-to-date account of principles, methods, and tools for mathematical and statistical modelling in a wide range of research fields, including medicine, health sciences, biology, environmental science, engineering, physics, chemistry, computation, finance, economics, and social sciences. It presents original solutions to real-world problems, emphasizes the coordinated development of theories and applications, and promotes interdisciplinary collaboration among mathematicians, statisticians, and researchers in other disciplines. Based on a highly successful meeting, the International Conference on Applied Mathematics, Modeling and Computational Science, AMMCS 2019, held from August 18 to 23, 2019, on the main campus of Wilfrid Laurier University, Waterloo, Canada, the contributions are the results of submissions from the conference participants. They provide readers with a broader view of the methods, ideas and tools used in mathematical, statistical and computational sciences.

Multivariate Statistical Modeling and Data Analysis

Author : H. Bozdogan,Arjun K. Gupta
Publisher : Springer Science & Business Media
Page : 193 pages
File Size : 55,8 Mb
Release : 2012-12-06
Category : Mathematics
ISBN : 9789400939776

Get Book

Multivariate Statistical Modeling and Data Analysis by H. Bozdogan,Arjun K. Gupta Pdf

This volume contains the Proceedings of the Advanced Symposium on Multivariate Modeling and Data Analysis held at the 64th Annual Heeting of the Virginia Academy of Sciences (VAS)--American Statistical Association's Vir ginia Chapter at James Madison University in Harrisonburg. Virginia during Hay 15-16. 1986. This symposium was sponsored by financial support from the Center for Advanced Studies at the University of Virginia to promote new and modern information-theoretic statist ical modeling procedures and to blend these new techniques within the classical theory. Multivariate statistical analysis has come a long way and currently it is in an evolutionary stage in the era of high-speed computation and computer technology. The Advanced Symposium was the first to address the new innovative approaches in multi variate analysis to develop modern analytical and yet practical procedures to meet the needs of researchers and the societal need of statistics. vii viii PREFACE Papers presented at the Symposium by e1l11lJinent researchers in the field were geared not Just for specialists in statistics, but an attempt has been made to achieve a well balanced and uniform coverage of different areas in multi variate modeling and data analysis. The areas covered included topics in the analysis of repeated measurements, cluster analysis, discriminant analysis, canonical cor relations, distribution theory and testing, bivariate densi ty estimation, factor analysis, principle component analysis, multidimensional scaling, multivariate linear models, nonparametric regression, etc.

Recent Advances in Mathematical and Statistical Methods

Author : D. Marc Kilgour,Herb Kunze,Roman Makarov
Publisher : Springer
Page : 662 pages
File Size : 53,9 Mb
Release : 2019-11-18
Category : Electronic
ISBN : 3030076261

Get Book

Recent Advances in Mathematical and Statistical Methods by D. Marc Kilgour,Herb Kunze,Roman Makarov Pdf

This book focuses on the recent development of methodologies and computation methods in mathematical and statistical modelling, computational science and applied mathematics. It emphasizes the development of theories and applications, and promotes interdisciplinary endeavour among mathematicians, statisticians, scientists, engineers and researchers from other disciplines. The book provides ideas, methods and tools in mathematical and statistical modelling that have been developed for a wide range of research fields, including medical, health sciences, biology, environmental science, engineering, physics and chemistry, finance, economics and social sciences. It presents original results addressing real-world problems. The contributions are products of a highly successful meeting held in August 2017 on the main campus of Wilfrid Laurier University, in Waterloo, Canada, the International Conference on Applied Mathematics, Modeling and Computational Science (AMMCS-2017). They make this book a valuable resource for readers interested not only in a broader overview of the methods, ideas and tools in mathematical and statistical approaches, but also in how they can attain valuable insights into problems arising in other disciplines.

Understanding Advanced Statistical Methods

Author : Peter Westfall,Kevin S. S. Henning
Publisher : CRC Press
Page : 572 pages
File Size : 52,9 Mb
Release : 2013-04-09
Category : Mathematics
ISBN : 9781466512108

Get Book

Understanding Advanced Statistical Methods by Peter Westfall,Kevin S. S. Henning Pdf

Providing a much-needed bridge between elementary statistics courses and advanced research methods courses, Understanding Advanced Statistical Methods helps students grasp the fundamental assumptions and machinery behind sophisticated statistical topics, such as logistic regression, maximum likelihood, bootstrapping, nonparametrics, and Bayesian methods. The book teaches students how to properly model, think critically, and design their own studies to avoid common errors. It leads them to think differently not only about math and statistics but also about general research and the scientific method. With a focus on statistical models as producers of data, the book enables students to more easily understand the machinery of advanced statistics. It also downplays the "population" interpretation of statistical models and presents Bayesian methods before frequentist ones. Requiring no prior calculus experience, the text employs a "just-in-time" approach that introduces mathematical topics, including calculus, where needed. Formulas throughout the text are used to explain why calculus and probability are essential in statistical modeling. The authors also intuitively explain the theory and logic behind real data analysis, incorporating a range of application examples from the social, economic, biological, medical, physical, and engineering sciences. Enabling your students to answer the why behind statistical methods, this text teaches them how to successfully draw conclusions when the premises are flawed. It empowers them to use advanced statistical methods with confidence and develop their own statistical recipes. Ancillary materials are available on the book’s website.

Advanced Mathematical Modeling with Technology

Author : William P. Fox,Robert E. Burks
Publisher : CRC Press
Page : 448 pages
File Size : 44,6 Mb
Release : 2021-05-20
Category : Mathematics
ISBN : 9781000388862

Get Book

Advanced Mathematical Modeling with Technology by William P. Fox,Robert E. Burks Pdf

Mathematical modeling is both a skill and an art and must be practiced in order to maintain and enhance the ability to use those skills. Though the topics covered in this book are the typical topics of most mathematical modeling courses, this book is best used for individuals or groups who have already taken an introductory mathematical modeling course. Advanced Mathematical Modeling with Technology will be of interest to instructors and students offering courses focused on discrete modeling or modeling for decision making. Each chapter begins with a problem to motivate the reader. The problem tells "what" the issue is or problem that needs to be solved. In each chapter, the authors apply the principles of mathematical modeling to that problem and present the steps in obtaining a model. The key focus is the mathematical model and the technology is presented as a method to solve that model or perform sensitivity analysis. We have selected , where applicable to the content because of their wide accessibility. The authors utilize technology to build, compute, or implement the model and then analyze the it. Features: MAPLE©, Excel©, and R© to support the mathematical modeling process. Excel templates, macros, and programs are available upon request from authors. Maple templates and example solution are also available. Includes coverage of mathematical programming. The power and limitations of simulations is covered. Introduces multi-attribute decision making (MADM) and game theory for solving problems. The book provides an overview to the decision maker of the wide range of applications of quantitative approaches to aid in the decision making process, and present a framework for decision making. Table of Contents 1. Perfect Partners: Mathematical Modeling and Technology 2. Review of Modeling with Discrete Dynamical Systems and Modeling Systems of DDS 3. Modeling with Differential Equations 4. Modeling System of Ordinary Differential Equation 5. Regression and Advanced Regression Methods and Models 6. Linear, Integer and Mixed Integer Programming 7. Nonlinear Optimization Methods 8. Multivariable Optimization 9. Simulation Models 10. Modeling Decision Making with Multi-Attribute Decision Modeling with Technology 11. Modeling with Game Theory 12. Appendix Using R Index Biographies Dr. William P. Fox is currently a visiting professor of Computational Operations Research at the College of William and Mary. He is an emeritus professor in the Department of Defense Analysis at the Naval Postgraduate School and teaches a three-course sequence in mathematical modeling for decision making. He received his Ph.D. in Industrial Engineering from Clemson University. He has taught at the United States Military Academy for twelve years until retiring and at Francis Marion University where he was the chair of mathematics for eight years. He has many publications and scholarly activities including twenty plus books and one hundred and fifty journal articles. Colonel (R) Robert E. Burks, Jr., Ph.D. is an Associate Professor in the Defense Analysis Department of the Naval Postgraduate School (NPS) and the Director of the NPS’ Wargaming Center. He holds a Ph.D. in Operations Research form the Air Force Institute of Technology. He is a retired logistics Army Colonel with more than thirty years of military experience in leadership, advanced analytics, decision modeling, and logistics operations who served as an Army Operations Research analyst at the Naval Postgraduate School, TRADOC Analysis Center, United States Military Academy, and the United States Army Recruiting Command.

Advanced Modelling in Mathematical Finance

Author : Jan Kallsen,Antonis Papapantoleon
Publisher : Springer
Page : 496 pages
File Size : 50,7 Mb
Release : 2016-12-01
Category : Mathematics
ISBN : 9783319458755

Get Book

Advanced Modelling in Mathematical Finance by Jan Kallsen,Antonis Papapantoleon Pdf

This Festschrift resulted from a workshop on “Advanced Modelling in Mathematical Finance” held in honour of Ernst Eberlein’s 70th birthday, from 20 to 22 May 2015 in Kiel, Germany. It includes contributions by several invited speakers at the workshop, including several of Ernst Eberlein’s long-standing collaborators and former students. Advanced mathematical techniques play an ever-increasing role in modern quantitative finance. Written by leading experts from academia and financial practice, this book offers state-of-the-art papers on the application of jump processes in mathematical finance, on term-structure modelling, and on statistical aspects of financial modelling. It is aimed at graduate students and researchers interested in mathematical finance, as well as practitioners wishing to learn about the latest developments.