Download or read book Accurate Case Outcome Modeling written by Arch G. Woodside and published by Springer Nature. This book was released on 2019-11-15 with total page 264 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume advocates accurate case outcome prediction that does not rely on symmetric modeling. To that end, it provides theory construction and testing applications in several sub-disciplines of business and the social sciences to illustrate how to move away from symmetric theory construction. Each chapter constructs case outcome theory and includes empirical analysis of outcomes. Chapter 1 provides a foundation of symmetric variable directional-relationship theory construction and null hypothesis significance testing versus asymmetric case outcome theory construction and somewhat precise outcome testing, while Chapters 2–6 investigate these principles through a range of applications. This volume will be very useful to researchers and professionals in manufacturing, service, consulting, management, marketing, organizational studies, and more. It will also be an excellent resource for advanced statistics students in building and testing case outcome models. Data sets are included so that readers can replicate findings presented in each chapter, and grow to present and test additional theories.
Download or read book Improving the Marriage of Modeling and Theory for Accurate Forecasts of Outcomes written by Arch G. Woodside and published by Emerald Group Publishing. This book was released on 2018-01-29 with total page 257 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book describes tools that are useful for decision-makers to improve their understanding of what is likely to happen in different configurations of contexts and decisions and to improve their forecasting abilities substantially.
Download or read book Regression Modeling Strategies written by Frank E. Harrell and published by Springer Science & Business Media. This book was released on 2013-03-09 with total page 583 pages. Available in PDF, EPUB and Kindle. Book excerpt: Many texts are excellent sources of knowledge about individual statistical tools, but the art of data analysis is about choosing and using multiple tools. Instead of presenting isolated techniques, this text emphasizes problem solving strategies that address the many issues arising when developing multivariable models using real data and not standard textbook examples. It includes imputation methods for dealing with missing data effectively, methods for dealing with nonlinear relationships and for making the estimation of transformations a formal part of the modeling process, methods for dealing with "too many variables to analyze and not enough observations," and powerful model validation techniques based on the bootstrap. This text realistically deals with model uncertainty and its effects on inference to achieve "safe data mining".
Download or read book Accuracy of Screeing Procedures Using Multilevel Modeling for Screening and Outcome Data written by Prashni Paliwal and published by . This book was released on 2004 with total page 262 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Intelligent Systems and Applications in Computer Vision written by Nitin Mittal and published by CRC Press. This book was released on 2023-11-02 with total page 341 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book comprehensively covers a wide range of evolutionary computer vision methods and applications, feature selection and extraction for training and classification, and metaheuristic algorithms in image processing. It further discusses optimized image segmentation, its analysis, pattern recognition, and object detection. Features: Discusses machine learning-based analytics such as GAN networks, autoencoders, computational imaging, and quantum computing Covers deep learning algorithms in computer vision Showcases novel solutions such as multi-resolution analysis in imaging processing, and metaheuristic algorithms for tackling challenges associated with image processing Highlight optimization problems such as image segmentation and minimized feature design vector Presents platform and simulation tools for image processing and segmentation The book aims to get the readers familiar with the fundamentals of computational intelligence as well as the recent advancements in related technologies like smart applications of digital images, and other enabling technologies from the context of image processing and computer vision. It further covers important topics such as image watermarking, steganography, morphological processing, and optimized image segmentation. It will serve as an ideal reference text for senior undergraduate, graduate students, and academic researchers in fields including electrical engineering, electronics, communications engineering, and computer engineering.
Download or read book Financial Modelling in Practice written by Michael Rees and published by John Wiley & Sons. This book was released on 2011-11-09 with total page 304 pages. Available in PDF, EPUB and Kindle. Book excerpt: Financial Modelling in Practice: A Concise Guide for Intermediate and Advanced Level is a practical, comprehensive and in-depth guide to financial modelling designed to cover the modelling issues that are relevant to facilitate the construction of robust and readily understandable models. Based on the authors extensive experience of building models in business and finance, and of training others how to do so this book starts with a review of Excel functions that are generally most relevant for building intermediate and advanced level models (such as Lookup functions, database and statistical functions and so on). It then discusses the principles involved in designing, structuring and building relevant, accurate and readily understandable models (including the use of sensitivity analysis techniques) before covering key application areas, such as the modelling of financial statements, of cash flow valuation, risk analysis, options and real options. Finally, the topic of financial modelling using VBA is treated. Practical examples are used throughout and model examples are included in the attached CD-ROM. Aimed at intermediate and advanced level modellers in Excel who wish to extend and consolidate their knowledge, this book is focused, practical, and application-driven, facilitating knowledge to build or audit a much wider range of financial models. Note: CD-ROM/DVD and other supplementary materials are not included as part of eBook file.
Download or read book Adaptive and Intelligent Systems written by Abdelhamid Bouchachia and published by Springer. This book was released on 2011-09-25 with total page 441 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the proceedings of the International Conference on Adaptive and Intelligent Systems, ICAIS 2011, held in Klagenfurt, Austria, in September 2011. The 36 full papers included in these proceedings together with the abstracts of 4 invited talks, were carefully reviewed and selected from 72 submissions. The contributions are organized under the following topical sections: incremental learning; adaptive system architecture; intelligent system engineering; data mining and pattern recognition; intelligent agents; and computational intelligence.
Download or read book New Methods for Improving Accuracy in Three Distinct Predictive Modeling Problems written by Yingying Xu and published by . This book was released on 2018 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: People are often interested in predicting a new or future observation. In clinical prediction, the uptake of Electronic Health Records (EHRs) has generated massive health datasets that are big in volume and diverse in variety. The outcomes can be of different types, e.g., continuous, binary, time-to-event, etc., and covariates can be either time-fixed or longitudinal. These datasets can provide rich and diverse information for modeling and prediction but also pose challenges to fast and accurate prediction of outcomes of interest. One challenge of predicting is that when the data are heterogeneous in the relationship between the covariates and the outcome. In this case, it is quite possible that localizing a subset of data in an informative manner to aid in making predictions will lead to better performance than including all information. Chapter 3 deals with a continuous outcome, and I have developed methodology that gives an interpretable and meaningful definition of similarity, and an algorithm to uncover the similarity structure to improve the prediction accuracy by making similarity-based predictions. In Chapter 4, the similarity-based prediction is extended to a survival outcome, with possible independent or dependent censoring. The algorithm is developed under the random forest framework, and I showed through both simulations and a real data example that incorporating the similarity structure indeed improves prediction accuracy in these cases. Another challenge in prediction arises when longitudinal covariates are present, and that there are scenarios when one needs to make an early prediction as soon as practical and thus cannot monitor the full trajectory of longitudinal covariates (before the prediction is required). In Chapter 5, I address this concern by quantifying the relationship between the earliness of prediction and the prediction accuracy. A penalization approach with a graphical method is introduced to select a monitoring window length given specific prediction accuracy. Comprehensive simulations are conducted to investigate the performance of the algorithm in selecting the length of the monitoring window in different scenarios.
Download or read book Principles and Practice of Structural Equation Modeling written by Rex B. Kline and published by Guilford Publications. This book was released on 2023-05-24 with total page 514 pages. Available in PDF, EPUB and Kindle. Book excerpt: Significantly revised, the fifth edition of the most complete, accessible text now covers all three approaches to structural equation modeling (SEM)--covariance-based SEM, nonparametric SEM (Pearl’s structural causal model), and composite SEM (partial least squares path modeling). With increased emphasis on freely available software tools such as the R lavaan package, the text uses data examples from multiple disciplines to provide a comprehensive understanding of all phases of SEM--what to know, best practices, and pitfalls to avoid. It includes exercises with answers, rules to remember, topic boxes, and a new self-test on significance testing, regression, and psychometrics. The companion website supplies helpful primers on these topics as well as data, syntax, and output for the book's examples, in files that can be opened with any basic text editor. New to This Edition *Chapters on composite SEM, also called partial least squares path modeling or variance-based SEM; conducting SEM analyses in small samples; and recent developments in mediation analysis. *Coverage of new reporting standards for SEM analyses; piecewise SEM, also called confirmatory path analysis; comparing alternative models fitted to the same data; and issues in multiple-group SEM. *Extended tutorials on techniques for dealing with missing data in SEM and instrumental variable methods to deal with confounding of target causal effects. Pedagogical Features *New self-test of knowledge about background topics (significance testing, regression, and psychometrics) with scoring key and online primers. *End-of-chapter suggestions for further reading and exercises with answers. *Troublesome examples from real data, with guidance for handling typical problems in analyses. *Topic boxes on special issues and boxed rules to remember. *Website promoting a learn-by-doing approach, including data, extensively annotated syntax, and output files for all the book’s detailed examples.
Download or read book Applied Predictive Modeling written by Max Kuhn and published by Springer Science & Business Media. This book was released on 2013-05-17 with total page 595 pages. Available in PDF, EPUB and Kindle. Book excerpt: Applied Predictive Modeling covers the overall predictive modeling process, beginning with the crucial steps of data preprocessing, data splitting and foundations of model tuning. The text then provides intuitive explanations of numerous common and modern regression and classification techniques, always with an emphasis on illustrating and solving real data problems. The text illustrates all parts of the modeling process through many hands-on, real-life examples, and every chapter contains extensive R code for each step of the process. This multi-purpose text can be used as an introduction to predictive models and the overall modeling process, a practitioner’s reference handbook, or as a text for advanced undergraduate or graduate level predictive modeling courses. To that end, each chapter contains problem sets to help solidify the covered concepts and uses data available in the book’s R package. This text is intended for a broad audience as both an introduction to predictive models as well as a guide to applying them. Non-mathematical readers will appreciate the intuitive explanations of the techniques while an emphasis on problem-solving with real data across a wide variety of applications will aid practitioners who wish to extend their expertise. Readers should have knowledge of basic statistical ideas, such as correlation and linear regression analysis. While the text is biased against complex equations, a mathematical background is needed for advanced topics.
Download or read book Dental Summary written by and published by . This book was released on 1913 with total page 1188 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Innovative Computing and Communications written by Aboul Ella Hassanien and published by Springer Nature. This book was released on with total page 694 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Clinical Prediction Models written by Ewout W. Steyerberg and published by Springer. This book was released on 2019-07-22 with total page 558 pages. Available in PDF, EPUB and Kindle. Book excerpt: The second edition of this volume provides insight and practical illustrations on how modern statistical concepts and regression methods can be applied in medical prediction problems, including diagnostic and prognostic outcomes. Many advances have been made in statistical approaches towards outcome prediction, but a sensible strategy is needed for model development, validation, and updating, such that prediction models can better support medical practice. There is an increasing need for personalized evidence-based medicine that uses an individualized approach to medical decision-making. In this Big Data era, there is expanded access to large volumes of routinely collected data and an increased number of applications for prediction models, such as targeted early detection of disease and individualized approaches to diagnostic testing and treatment. Clinical Prediction Models presents a practical checklist that needs to be considered for development of a valid prediction model. Steps include preliminary considerations such as dealing with missing values; coding of predictors; selection of main effects and interactions for a multivariable model; estimation of model parameters with shrinkage methods and incorporation of external data; evaluation of performance and usefulness; internal validation; and presentation formatting. The text also addresses common issues that make prediction models suboptimal, such as small sample sizes, exaggerated claims, and poor generalizability. The text is primarily intended for clinical epidemiologists and biostatisticians. Including many case studies and publicly available R code and data sets, the book is also appropriate as a textbook for a graduate course on predictive modeling in diagnosis and prognosis. While practical in nature, the book also provides a philosophical perspective on data analysis in medicine that goes beyond predictive modeling. Updates to this new and expanded edition include: • A discussion of Big Data and its implications for the design of prediction models • Machine learning issues • More simulations with missing ‘y’ values • Extended discussion on between-cohort heterogeneity • Description of ShinyApp • Updated LASSO illustration • New case studies
Download or read book Handbook of Police Psychology written by Jack Kitaeff and published by Routledge. This book was released on 2019-06-11 with total page 652 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Handbook of Police Psychology features contributions from over 30 leading experts on the core matters of police psychology. The collection surveys everything from the beginnings of police psychology and early influences on the profession; to pre-employment screening, assessment, and evaluation; to clinical interventions. Alongside original chapters first published in 2011, this edition features new content on deadly force encounters, officer resilience training, and police leadership enhancement. Influential figures in the field of police psychology are discussed, including America’s first full-time police psychologist, who served in the Los Angeles Police Department, and the first full-time police officer to earn a doctorate in psychology while still in uniform, who served with the New York Police Department. The Handbook of Police Psychology is an invaluable resource for police legal advisors, policy writers, and police psychologists, as well as for graduates studying police or forensic psychology.
Download or read book Business Process Management written by Chiara Di Francescomarino and published by Springer Nature. This book was released on 2023-08-31 with total page 510 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 21st International Conference on Business Process Management, BPM 2023, which took place in Utrecht, The Netherlands, in September 2023. The 27 papers included in this book were carefully reviewed and selected from 151 submissions. They were organized in three main research tracks: Foundations, engineering, and management.
Download or read book Advances in Conceptual Modeling written by Georg Grossmann and published by Springer Nature. This book was released on 2020-12-21 with total page 252 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of five workshops symposia, held at the 39th International Conference on Conceptual Modeling, ER 2020, which were supposed to be held in Vienna, Austria, in November 2020, but were held virtually due to the COVID-19 pandemic instead. The 20 papers promote and disseminate research on theories of concepts underlying conceptual modeling, methods and tools for developing and communicating conceptual models, techniques for transforming conceptual models into effective implementations, and the impact of conceptual modeling techniques on databases, business strategies and information systems. The following workshops are included in this volume: First Workshop on Conceptual Modeling Meets Artificial Intelligence and Data-Driven Decision Making (CMAI); First International Workshop on Conceptual Modeling for Life Sciences (CMLS); Second Workshop on Conceptual Modeling, Ontologies and (Meta)data Management for Findable, Accessible, Interoperable and Reusable (FAIR) Data (CMOMM4FAIR); First Workshop on Conceptual Modeling for NoSQL Data Stores (CoMoNoS); and Third International Workshop on Empirical Methods in Conceptual Modeling (EmpER).
Download or read book Land Seismic Case Studies for Near Surface Modeling and Subsurface Imaging written by Öz Yilmaz and published by SEG Books. This book was released on 2021-06-30 with total page 1056 pages. Available in PDF, EPUB and Kindle. Book excerpt: Written for practicing geophysicists, “Land Seismic Case Studies for Near-Surface Modeling and Subsurface Imaging” is a comprehensive guide to understanding and interpreting seismic data. The culmination of land seismic data acquisition and processing projects conducted by the author over the last two decades, this book contains more than nearly 800 figures from worldwide case studies—conducted in both 2D and 3D. Beginning with Chapter 1 on seismic characterization of the near-surface, Chapter 2 presents near-surface modeling by traveltime and full-wave inversion, Chapter 3 presents near-surface modeling by imaging, and then Chapter 4 includes detailed case studies for near-surface modeling. Chapter 5 reviews single- and multichannel signal processing of land seismic data with the key objective of removing surface waves and guided waves that are characterized as coherent linear noise. Uncommon seismic data acquisition methods, including large-offset acquisition in thrust belts to capture the large-amplitude supercritical reflections, swath-line acquisition, and joint PP and SH- SH seismic imaging are highlighted in Chapter 6, and Chapter 7 presents image-based rms velocity estimation and discusses the problem of velocity uncertainty. The final two chapters focus exclusively on case studies: 2D in Chapter 8 and 3D in Chapter 9. An outstanding teaching tool, this book includes analysis workflows containing processing steps designed to solve specific problems. Essential for anyone involved in acquisition, processing, and inversion of seismic data, this volume will become the definitive reference for understanding how the variables in seismic acquisition are directly reflected in the data.
