Download or read book Statistical Modeling and Applications on Real Time Problems written by Chandra Shekhar and published by CRC Press. This book was released on 2024-06-06 with total page 249 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Statistical Modeling and Applications on Real Time Problems written by Chandra Shekhar and published by CRC Press. This book was released on 2024-06-06 with total page 195 pages. Available in PDF, EPUB and Kindle. Book excerpt: In the dynamic landscape of modern data analysis, this curated guide by global experts explores the latest in statistical methodologies, modeling techniques, and optimization strategies. This comprehensive text offers insights into diverse fields such as engineering, economics, medicine, and agriculture, addressing real-world challenges. It delves into the intricacies of the Lomax distribution under a Type II censoring scheme, exploring various loss functions. The compilation uncovers estimators for population proportion, product of two population means, and more, supported by empirical and simulation studies. Additionally, it scrutinizes the prevalence of caesarean section deliveries in India, correlating with socio-economic factors. This book · Traverses diverse fields for insights into real-world challenges. · Delves into the intricacies of the Lomax distribution under a Type II censoring scheme. · Uncovers estimators supported by empirical and simulation studies. · Scrutinizes the prevalence of caesarean section deliveries in India, correlating with socio-economic factors. This compilation promises a holistic exploration of advanced statistical and optimization methods, offering readers valuable insights into their pragmatic applications across a spectrum of real-world issues.
Download or read book Mathematical Modeling and Computation of Real Time Problems written by Rakhee Kulshrestha and published by CRC Press. This book was released on 2021-01-04 with total page 172 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book covers an interdisciplinary approach for understanding mathematical modeling by offering a collection of models, solved problems related to the models, the methodologies employed, and the results using projects and case studies with insight into the operation of substantial real-time systems. The book covers a broad scope in the areas of statistical science, probability, stochastic processes, fluid dynamics, supply chain, optimization, and applications. It discusses advanced topics and the latest research findings, uses an interdisciplinary approach for real-time systems, offers a platform for integrated research, and identifies the gaps in the field for further research. The book is for researchers, students, and teachers that share a goal of learning advanced topics and the latest research in mathematical modeling.
Download or read book Statistical Software Engineering written by National Research Council and published by National Academies Press. This book was released on 1996-03-15 with total page 83 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book identifies challenges and opportunities in the development and implementation of software that contain significant statistical content. While emphasizing the relevance of using rigorous statistical and probabilistic techniques in software engineering contexts, it presents opportunities for further research in the statistical sciences and their applications to software engineering. It is intended to motivate and attract new researchers from statistics and the mathematical sciences to attack relevant and pressing problems in the software engineering setting. It describes the "big picture," as this approach provides the context in which statistical methods must be developed. The book's survey nature is directed at the mathematical sciences audience, but software engineers should also find the statistical emphasis refreshing and stimulating. It is hoped that the book will have the effect of seeding the field of statistical software engineering by its indication of opportunities where statistical thinking can help to increase understanding, productivity, and quality of software and software production.
Download or read book Statistical Data Modeling and Machine Learning with Applications written by Snezhana Gocheva-Ilieva and published by . This book was released on 2021 with total page 184 pages. Available in PDF, EPUB and Kindle. Book excerpt: The modeling and processing of empirical data is one of the main subjects and goals of statistics. Nowadays, with the development of computer science, the extraction of useful and often hidden information and patterns from data sets of different volumes and complex data sets in warehouses has been added to these goals. New and powerful statistical techniques with machine learning (ML) and data mining paradigms have been developed. To one degree or another, all of these techniques and algorithms originate from a rigorous mathematical basis, including probability theory and mathematical statistics, operational research, mathematical analysis, numerical methods, etc. Popular ML methods, such as artificial neural networks (ANN), support vector machines (SVM), decision trees, random forest (RF), among others, have generated models that can be considered as straightforward applications of optimization theory and statistical estimation. The wide arsenal of classical statistical approaches combined with powerful ML techniques allows many challenging and practical problems to be solved. This Special Issue belongs to the section “Mathematics and Computer Science”. Its aim is to establish a brief collection of carefully selected papers presenting new and original methods, data analyses, case studies, comparative studies, and other research on the topic of statistical data modeling and ML as well as their applications. Particular attention is given, but is not limited, to theories and applications in diverse areas such as computer science, medicine, engineering, banking, education, sociology, economics, among others. The resulting palette of methods, algorithms, and applications for statistical modeling and ML presented in this Special Issue is expected to contribute to the further development of research in this area. We also believe that the new knowledge acquired here as well as the applied results are attractive and useful for young scientists, doctoral students, and researchers from various scientific specialties.
Download or read book Statistical Modeling and Computation written by Dirk P. Kroese and published by Springer Science & Business Media. This book was released on 2013-11-18 with total page 412 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Statistical Modeling and Analysis for Complex Data Problems written by Pierre Duchesne and published by Springer Science & Business Media. This book was released on 2005-04-12 with total page 354 pages. Available in PDF, EPUB and Kindle. Book excerpt: STATISTICAL MODELING AND ANALYSIS FOR COMPLEX DATA PROBLEMS treats some of today’s more complex problems and it reflects some of the important research directions in the field. Twenty-nine authors—largely from Montreal’s GERAD Multi-University Research Center and who work in areas of theoretical statistics, applied statistics, probability theory, and stochastic processes—present survey chapters on various theoretical and applied problems of importance and interest to researchers and students across a number of academic domains. Some of the areas and topics examined in the volume are: an analysis of complex survey data, the 2000 American presidential election in Florida, data mining, estimation of uncertainty for machine learning algorithms, interacting stochastic processes, dependent data & copulas, Bayesian analysis of hazard rates, re-sampling methods in a periodic replacement problem, statistical testing in genetics and for dependent data, statistical analysis of time series analysis, theoretical and applied stochastic processes, and an efficient non linear filtering algorithm for the position detection of multiple targets. The book examines the methods and problems from a modeling perspective and surveys the state of current research on each topic and provides direction for further research exploration of the area.
Download or read book Advances in Statistical Methodologies and Their Application to Real Problems written by Tsukasa Hokimoto and published by BoD – Books on Demand. This book was released on 2017-04-26 with total page 327 pages. Available in PDF, EPUB and Kindle. Book excerpt: In recent years, statistical techniques and methods for data analysis have advanced significantly in a wide range of research areas. These developments enable researchers to analyze increasingly large datasets with more flexibility and also more accurately estimate and evaluate the phenomena they study. We recognize the value of recent advances in data analysis techniques in many different research fields. However, we also note that awareness of these different statistical and probabilistic approaches may vary, owing to differences in the datasets typical of different research fields. This book provides a cross-disciplinary forum for exploring the variety of new data analysis techniques emerging from different fields.
Download or read book Statistical Modeling written by William Steve Mallios and published by Wiley-Blackwell. This book was released on 1989 with total page 256 pages. Available in PDF, EPUB and Kindle. Book excerpt: Textbook for graduate level courses in applied modeling. Demonstrates the relevance of statistics in the late 20th century and the value of such modeling to the decision support system. Includes an overview of Bayesian discriminate analysis and regression systems. Annotation copyright Book News, Inc
Download or read book Mathematical and Statistical Models and Methods in Reliability written by V.V. Rykov and published by Springer Science & Business Media. This book was released on 2010-11-02 with total page 465 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Advanced Statistics with Applications in R written by Eugene Demidenko and published by John Wiley & Sons. This book was released on 2019-11-12 with total page 880 pages. Available in PDF, EPUB and Kindle. Book excerpt: Advanced Statistics with Applications in R fills the gap between several excellent theoretical statistics textbooks and many applied statistics books where teaching reduces to using existing packages. This book looks at what is under the hood. Many statistics issues including the recent crisis with p-value are caused by misunderstanding of statistical concepts due to poor theoretical background of practitioners and applied statisticians. This book is the product of a forty-year experience in teaching of probability and statistics and their applications for solving real-life problems. There are more than 442 examples in the book: basically every probability or statistics concept is illustrated with an example accompanied with an R code. Many examples, such as Who said π? What team is better? The fall of the Roman empire, James Bond chase problem, Black Friday shopping, Free fall equation: Aristotle or Galilei, and many others are intriguing. These examples cover biostatistics, finance, physics and engineering, text and image analysis, epidemiology, spatial statistics, sociology, etc. Advanced Statistics with Applications in R teaches students to use theory for solving real-life problems through computations: there are about 500 R codes and 100 datasets. These data can be freely downloaded from the author's website dartmouth.edu/~eugened. This book is suitable as a text for senior undergraduate students with major in statistics or data science or graduate students. Many researchers who apply statistics on the regular basis find explanation of many fundamental concepts from the theoretical perspective illustrated by concrete real-world applications.
Download or read book Catalogue of the University of Michigan written by University of Michigan and published by . This book was released on 1967 with total page 852 pages. Available in PDF, EPUB and Kindle. Book excerpt: Announcements for the following year included in some vols.
Download or read book University of Michigan Official Publication written by and published by UM Libraries. This book was released on 1965 with total page 1400 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Mathematical Modeling and Computation of Real Time Problems written by Rakhee Kulshrestha and published by CRC Press. This book was released on 2021-01-03 with total page 234 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book covers an interdisciplinary approach for understanding mathematical modeling by offering a collection of models, solved problems related to the models, the methodologies employed, and the results using projects and case studies with insight into the operation of substantial real-time systems. The book covers a broad scope in the areas of statistical science, probability, stochastic processes, fluid dynamics, supply chain, optimization, and applications. It discusses advanced topics and the latest research findings, uses an interdisciplinary approach for real-time systems, offers a platform for integrated research, and identifies the gaps in the field for further research. The book is for researchers, students, and teachers that share a goal of learning advanced topics and the latest research in mathematical modeling.
Download or read book General Register written by University of Michigan and published by . This book was released on 1966 with total page 1318 pages. Available in PDF, EPUB and Kindle. Book excerpt: Announcements for the following year included in some vols.
Download or read book Statistical Modeling in Machine Learning written by Tilottama Goswami and published by Academic Press. This book was released on 2022-10-29 with total page 398 pages. Available in PDF, EPUB and Kindle. Book excerpt: Statistical Modeling in Machine Learning: Concepts and Applications presents the basic concepts and roles of statistics, exploratory data analysis and machine learning. The various aspects of Machine Learning are discussed along with basics of statistics. Concepts are presented with simple examples and graphical representation for better understanding of techniques. This book takes a holistic approach – putting key concepts together with an in-depth treatise on multi-disciplinary applications of machine learning. New case studies and research problem statements are discussed, which will help researchers in their application areas based on the concepts of statistics and machine learning. Statistical Modeling in Machine Learning: Concepts and Applications will help statisticians, machine learning practitioners and programmers solving various tasks such as classification, regression, clustering, forecasting, recommending and more. Provides a comprehensive overview of the state-of-the-art in statistical concepts applied to Machine Learning with the help of real-life problems, applications and tutorials Presents a step-by-step approach from fundamentals to advanced techniques Includes Case Studies with both successful and unsuccessful applications of Machine Learning to understand challenges in its implementation, along with worked examples
Download or read book Springer Handbook of Engineering Statistics written by Hoang Pham and published by Springer Nature. This book was released on 2023-04-20 with total page 1136 pages. Available in PDF, EPUB and Kindle. Book excerpt: In today’s global and highly competitive environment, continuous improvement in the processes and products of any field of engineering is essential for survival. This book gathers together the full range of statistical techniques required by engineers from all fields. It will assist them to gain sensible statistical feedback on how their processes or products are functioning and to give them realistic predictions of how these could be improved. The handbook will be essential reading for all engineers and engineering-connected managers who are serious about keeping their methods and products at the cutting edge of quality and competitiveness.
