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Risk Moddelling And Survival Analysis


Risk Moddelling And Survival Analysis
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Risk Moddelling And Survival Analysis


Risk Moddelling And Survival Analysis
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Author : Mr. Rohit Manglik
language : en
Publisher: EduGorilla Publication
Release Date : 2024-06-28

Risk Moddelling And Survival Analysis written by Mr. Rohit Manglik and has been published by EduGorilla Publication this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-06-28 with Business & Economics categories.


EduGorilla Publication is a trusted name in the education sector, committed to empowering learners with high-quality study materials and resources. Specializing in competitive exams and academic support, EduGorilla provides comprehensive and well-structured content tailored to meet the needs of students across various streams and levels.



Ifrs 9 And Cecl Credit Risk Modelling And Validation


Ifrs 9 And Cecl Credit Risk Modelling And Validation
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Author : Tiziano Bellini
language : en
Publisher: Academic Press
Release Date : 2019-01-15

Ifrs 9 And Cecl Credit Risk Modelling And Validation written by Tiziano Bellini and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-01-15 with Business & Economics categories.


IFRS 9 and CECL Credit Risk Modelling and Validation covers a hot topic in risk management. Both IFRS 9 and CECL accounting standards require Banks to adopt a new perspective in assessing Expected Credit Losses. The book explores a wide range of models and corresponding validation procedures. The most traditional regression analyses pave the way to more innovative methods like machine learning, survival analysis, and competing risk modelling. Special attention is then devoted to scarce data and low default portfolios. A practical approach inspires the learning journey. In each section the theoretical dissertation is accompanied by Examples and Case Studies worked in R and SAS, the most widely used software packages used by practitioners in Credit Risk Management. - Offers a broad survey that explains which models work best for mortgage, small business, cards, commercial real estate, commercial loans and other credit products - Concentrates on specific aspects of the modelling process by focusing on lifetime estimates - Provides an hands-on approach to enable readers to perform model development, validation and audit of credit risk models



Lifetime Data Models In Reliability And Survival Analysis


Lifetime Data Models In Reliability And Survival Analysis
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Author : Nicholas P. Jewell
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-04-17

Lifetime Data Models In Reliability And Survival Analysis written by Nicholas P. Jewell 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 2013-04-17 with Mathematics categories.


Statistical models and methods for lifetime and other time-to-event data are widely used in many fields, including medicine, the environmental sciences, actuarial science, engineering, economics, management, and the social sciences. For example, closely related statistical methods have been applied to the study of the incubation period of diseases such as AIDS, the remission time of cancers, life tables, the time-to-failure of engineering systems, employment duration, and the length of marriages. This volume contains a selection of papers based on the 1994 International Research Conference on Lifetime Data Models in Reliability and Survival Analysis, held at Harvard University. The conference brought together a varied group of researchers and practitioners to advance and promote statistical science in the many fields that deal with lifetime and other time-to-event-data. The volume illustrates the depth and diversity of the field. A few of the authors have published their conference presentations in the new journal Lifetime Data Analysis (Kluwer Academic Publishers).



Analyzing Risk Through Probabilistic Modeling In Operations Research


Analyzing Risk Through Probabilistic Modeling In Operations Research
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Author : Jakóbczak, Dariusz Jacek
language : en
Publisher: IGI Global
Release Date : 2015-11-03

Analyzing Risk Through Probabilistic Modeling In Operations Research written by Jakóbczak, Dariusz Jacek and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-11-03 with Business & Economics categories.


Probabilistic modeling represents a subject spanning many branches of mathematics, economics, and computer science to connect pure mathematics with applied sciences. Operational research also relies on this connection to enable the improvement of business functions and decision making. Analyzing Risk through Probabilistic Modeling in Operations Research is an authoritative reference publication discussing the various challenges in management and decision science. Featuring exhaustive coverage on a range of topics within operational research including, but not limited to, decision analysis, data mining, process modeling, probabilistic interpolation and extrapolation, and optimization methods, this book is an essential reference source for decision makers, academicians, researchers, advanced-level students, technology developers, and government officials interested in the implementation of probabilistic modeling in various business applications.



Subject Cs2


Subject Cs2
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Author : Institute and Faculty of Actuaries
language : en
Publisher:
Release Date : 2020

Subject Cs2 written by Institute and Faculty of Actuaries and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020 with Insurance categories.




Absolute Risk


Absolute Risk
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Author : Ruth M. Pfeiffer
language : en
Publisher: CRC Press
Release Date : 2017-08-10

Absolute Risk written by Ruth M. Pfeiffer and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-08-10 with Mathematics categories.


Absolute Risk: Methods and Applications in Clinical Management and Public Health provides theory and examples to demonstrate the importance of absolute risk in counseling patients, devising public health strategies, and clinical management. The book provides sufficient technical detail to allow statisticians, epidemiologists, and clinicians to build, test, and apply models of absolute risk. Features: Provides theoretical basis for modeling absolute risk, including competing risks and cause-specific and cumulative incidence regression Discusses various sampling designs for estimating absolute risk and criteria to evaluate models Provides details on statistical inference for the various sampling designs Discusses criteria for evaluating risk models and comparing risk models, including both general criteria and problem-specific expected losses in well-defined clinical and public health applications Describes many applications encompassing both disease prevention and prognosis, and ranging from counseling individual patients, to clinical decision making, to assessing the impact of risk-based public health strategies Discusses model updating, family-based designs, dynamic projections, and other topics Ruth M. Pfeiffer is a mathematical statistician and Fellow of the American Statistical Association, with interests in risk modeling, dimension reduction, and applications in epidemiology. She developed absolute risk models for breast cancer, colon cancer, melanoma, and second primary thyroid cancer following a childhood cancer diagnosis. Mitchell H. Gail developed the widely used "Gail model" for projecting the absolute risk of invasive breast cancer. He is a medical statistician with interests in statistical methods and applications in epidemiology and molecular medicine. He is a member of the National Academy of Medicine and former President of the American Statistical Association. Both are Senior Investigators in the Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health.



Credit Scoring And Its Applications Second Edition


Credit Scoring And Its Applications Second Edition
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Author : Lyn Thomas
language : en
Publisher: SIAM
Release Date : 2017-08-16

Credit Scoring And Its Applications Second Edition written by Lyn Thomas and has been published by SIAM this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-08-16 with Business & Economics categories.


Credit Scoring and Its Applications?is recognized as the bible of credit scoring. It contains a comprehensive review of the objectives, methods, and practical implementation of credit and behavioral scoring. The authors review principles of the statistical and operations research methods used in building scorecards, as well as the advantages and disadvantages of each approach. The book contains a description of practical problems encountered in building, using, and monitoring scorecards and examines some of the country-specific issues in bankruptcy, equal opportunities, and privacy legislation. It contains a discussion of economic theories of consumers' use of credit, and readers will gain an understanding of what lending institutions seek to achieve by using credit scoring and the changes in their objectives.? New to the second edition are lessons that can be learned for operations research model building from the global financial crisis, current applications of scoring, discussions on the Basel Accords and their requirements for scoring, new methods for scorecard building and new expanded sections on ways of measuring scorecard performance. And survival analysis for credit scoring. Other unique features include methods of monitoring scorecards and deciding when to update them, as well as different applications of scoring, including direct marketing, profit scoring, tax inspection, prisoner release, and payment of fines.?



Risk Assessment And Evaluation Of Predictions


Risk Assessment And Evaluation Of Predictions
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Author : Mei-Ling Ting Lee
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-12-11

Risk Assessment And Evaluation Of Predictions written by Mei-Ling Ting Lee 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 2013-12-11 with Medical categories.


Methods of risk analysis and the outcome of particular evaluations and predictions are covered in detail in this proceedings volume, whose contributions are based on invited presentations from Professor Mei-Ling Ting Lee's 2011 symposium on Risk Analysis and the Evaluation of Predictions. This symposium was held at the University of Maryland in October of 2011. Risk analysis is the science of evaluating health, environmental, and engineering risks resulting from past, current, or anticipated, future activities. The use of these evaluations include to provide information for determining regulatory actions to limit risk, present scientific evidence in legal settings, evaluate products and potential liabilities within private organizations, resolve World Trade disputes amongst nations, and educate the public concerning particular risk issues. Risk analysis is an interdisciplinary science that relies on epidemiology and laboratory studies, collection of exposure and other field data, computer modeling, and related social, economic and communication considerations. In addition, social dimensions of risk are addressed by social scientists.



Bayesian Hierarchical Models


Bayesian Hierarchical Models
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Author : Peter D. Congdon
language : en
Publisher: CRC Press
Release Date : 2019-09-16

Bayesian Hierarchical Models written by Peter D. Congdon and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-09-16 with Mathematics categories.


An intermediate-level treatment of Bayesian hierarchical models and their applications, this book demonstrates the advantages of a Bayesian approach to data sets involving inferences for collections of related units or variables, and in methods where parameters can be treated as random collections. Through illustrative data analysis and attention to statistical computing, this book facilitates practical implementation of Bayesian hierarchical methods. The new edition is a revision of the book Applied Bayesian Hierarchical Methods. It maintains a focus on applied modelling and data analysis, but now using entirely R-based Bayesian computing options. It has been updated with a new chapter on regression for causal effects, and one on computing options and strategies. This latter chapter is particularly important, due to recent advances in Bayesian computing and estimation, including the development of rjags and rstan. It also features updates throughout with new examples. The examples exploit and illustrate the broader advantages of the R computing environment, while allowing readers to explore alternative likelihood assumptions, regression structures, and assumptions on prior densities. Features: Provides a comprehensive and accessible overview of applied Bayesian hierarchical modelling Includes many real data examples to illustrate different modelling topics R code (based on rjags, jagsUI, R2OpenBUGS, and rstan) is integrated into the book, emphasizing implementation Software options and coding principles are introduced in new chapter on computing Programs and data sets available on the book’s website



Bayesian Approaches In Oncology Using R And Openbugs


Bayesian Approaches In Oncology Using R And Openbugs
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Author : Atanu Bhattacharjee
language : en
Publisher: CRC Press
Release Date : 2020-12-14

Bayesian Approaches In Oncology Using R And Openbugs written by Atanu Bhattacharjee and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-12-14 with Mathematics categories.


Bayesian Approaches in Oncology Using R and OpenBUGS serves two audiences: those who are familiar with the theory and applications of bayesian approach and wish to learn or enhance their skills in R and OpenBUGS, and those who are enrolled in R and OpenBUGS-based course for bayesian approach implementation. For those who have never used R/OpenBUGS, the book begins with a self-contained introduction to R that lays the foundation for later chapters. Many books on the bayesian approach and the statistical analysis are advanced, and many are theoretical. While most of them do cover the objective, the fact remains that data analysis can not be performed without actually doing it, and this means using dedicated statistical software. There are several software packages, all with their specific objective. Finally, all packages are free to use, are versatile with problem-solving, and are interactive with R and OpenBUGS. This book continues to cover a range of techniques related to oncology that grow in statistical analysis. It intended to make a single source of information on Bayesian statistical methodology for oncology research to cover several dimensions of statistical analysis. The book explains data analysis using real examples and includes all the R and OpenBUGS codes necessary to reproduce the analyses. The idea is to overall extending the Bayesian approach in oncology practice. It presents four sections to the statistical application framework: Bayesian in Clinical Research and Sample Size Calcuation Bayesian in Time-to-Event Data Analysis Bayesian in Longitudinal Data Analysis Bayesian in Diagnostics Test Statistics This book is intended as a first course in bayesian biostatistics for oncology students. An oncologist can find useful guidance for implementing bayesian in research work. It serves as a practical guide and an excellent resource for learning the theory and practice of bayesian methods for the applied statistician, biostatistician, and data scientist.