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Book Synopsis Predictive Modeling Applications in Actuarial Science by : Edward W. Frees
Download or read book Predictive Modeling Applications in Actuarial Science written by Edward W. Frees and published by Cambridge University Press. This book was released on 2014-07-28 with total page 565 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is for actuaries and financial analysts developing their expertise in statistics and who wish to become familiar with concrete examples of predictive modeling.
Book Synopsis Solutions Manual for Actuarial Mathematics for Life Contingent Risks by : David C. M. Dickson
Download or read book Solutions Manual for Actuarial Mathematics for Life Contingent Risks written by David C. M. Dickson and published by Cambridge University Press. This book was released on 2012-03-26 with total page 180 pages. Available in PDF, EPUB and Kindle. Book excerpt: "This manual presents solutions to all exercises from Actuarial Mathematics for Life Contingent Risks (AMLCR) by David C.M. Dickson, Mary R. Hardy, Howard Waters; Cambridge University Press, 2009. ISBN 9780521118255"--Pref.
Book Synopsis Predictive Modeling Applications in Actuarial Science by :
Download or read book Predictive Modeling Applications in Actuarial Science written by and published by . This book was released on with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Predictive Modeling Applications in Actuarial Science: Volume 2, Case Studies in Insurance by : Edward W. Frees
Download or read book Predictive Modeling Applications in Actuarial Science: Volume 2, Case Studies in Insurance written by Edward W. Frees and published by Cambridge University Press. This book was released on 2016-07-27 with total page 337 pages. Available in PDF, EPUB and Kindle. Book excerpt: Predictive modeling uses data to forecast future events. It exploits relationships between explanatory variables and the predicted variables from past occurrences to predict future outcomes. Forecasting financial events is a core skill that actuaries routinely apply in insurance and other risk-management applications. Predictive Modeling Applications in Actuarial Science emphasizes life-long learning by developing tools in an insurance context, providing the relevant actuarial applications, and introducing advanced statistical techniques that can be used to gain a competitive advantage in situations with complex data. Volume 2 examines applications of predictive modeling. Where Volume 1 developed the foundations of predictive modeling, Volume 2 explores practical uses for techniques, focusing on property and casualty insurance. Readers are exposed to a variety of techniques in concrete, real-life contexts that demonstrate their value and the overall value of predictive modeling, for seasoned practicing analysts as well as those just starting out.
Book Synopsis Regression Modeling with Actuarial and Financial Applications by : Edward W. Frees
Download or read book Regression Modeling with Actuarial and Financial Applications written by Edward W. Frees and published by Cambridge University Press. This book was released on 2010 with total page 585 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book teaches multiple regression and time series and how to use these to analyze real data in risk management and finance.
Book Synopsis Predictive Modeling Applications in Actuarial Science by :
Download or read book Predictive Modeling Applications in Actuarial Science written by and published by . This book was released on 2016 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: "The International Series on Actuarial Science, published by Cambridge University Press in con-junction with the Institute and Faculty of Actuaries, contains textbooks for students taking courses in or related to actuarial science, as well as more advanced works designed for continuing pro-fessional development or for describing and synthesizing research. The series is a vehicle for publishing books that reflect changes and developments in the curriculum, that encourage the introduction of courses on actuarial science in universities, and that show how actuarial science can be used in all areas where there is long-term financial risk"--
Book Synopsis Predictive Modeling Applications in Actuarial Science: Volume 2, Case Studies in Insurance by : Edward W. Frees
Download or read book Predictive Modeling Applications in Actuarial Science: Volume 2, Case Studies in Insurance written by Edward W. Frees and published by Cambridge University Press. This book was released on 2016-07-27 with total page 330 pages. Available in PDF, EPUB and Kindle. Book excerpt: Predictive modeling uses data to forecast future events. It exploits relationships between explanatory variables and the predicted variables from past occurrences to predict future outcomes. Forecasting financial events is a core skill that actuaries routinely apply in insurance and other risk-management applications. Predictive Modeling Applications in Actuarial Science emphasizes life-long learning by developing tools in an insurance context, providing the relevant actuarial applications, and introducing advanced statistical techniques that can be used to gain a competitive advantage in situations with complex data. Volume 2 examines applications of predictive modeling. Where Volume 1 developed the foundations of predictive modeling, Volume 2 explores practical uses for techniques, focusing on property and casualty insurance. Readers are exposed to a variety of techniques in concrete, real-life contexts that demonstrate their value and the overall value of predictive modeling, for seasoned practicing analysts as well as those just starting out.
Book Synopsis Applied Predictive Modeling by : Max Kuhn
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 600 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.
Book Synopsis Systems Science and Modeling for Ecological Economics by : Alexey A. Voinov
Download or read book Systems Science and Modeling for Ecological Economics written by Alexey A. Voinov and published by Academic Press. This book was released on 2010-07-27 with total page 432 pages. Available in PDF, EPUB and Kindle. Book excerpt: Modeling is a key component to sciences from mathematics to life science, including environmental and ecological studies. By looking at the underlying concepts of the software, we can make sure that we build mathematically feasible models and that we get the most out of the data and information that we have. Systems Science and Modeling for Ecological Economics shows how models can be analyzed using simple math and software to generate meaningful qualitative descriptions of system dynamics. This book shows that even without a full analytical, mathematically rigorous analysis of the equations, there may be ways to derive some qualitative understanding of the general behavior of a system. By relating some of the modeling approaches and systems theory to real-world examples the book illustrates how these approaches can help understand concepts such as sustainability, peak oil, adaptive management, optimal harvest and other practical applications. Relates modeling approaches and systems theory to real-world examples Teaches students to build mathematically feasible models and get the most out of the data and information available Wide range of applications in hydrology, population dynamics, market cycles, sustainability theory, management, and more
Book Synopsis Predictive Modeling Applications in Actuarial Science by : Edward W. Frees
Download or read book Predictive Modeling Applications in Actuarial Science written by Edward W. Frees and published by . This book was released on 2014 with total page 330 pages. Available in PDF, EPUB and Kindle. Book excerpt: Predictive modeling uses data to forecast future events. It exploits relationships between explanatory variables and the predicted variables from past occurrences to predict future outcomes. Forecasting financial events is a core skill that actuaries routinely apply in insurance and other risk-management applications. Predictive Modeling Applications in Actuarial Science emphasizes life-long learning by developing tools in an insurance context, providing the relevant actuarial applications, and introducing advanced statistical techniques that can be used to gain a competitive advantage in situations with complex data. Volume 2 examines applications of predictive modeling. Where Volume 1 developed the foundations of predictive modeling, Volume 2 explores practical uses for techniques, focusing on property and casualty insurance. Readers are exposed to a variety of techniques in concrete, real-life contexts that demonstrate their value and the overall value of predictive modeling, for seasoned practicing analysts as well as those just starting out.
Book Synopsis Generalized Linear Models for Insurance Data by : Piet de Jong
Download or read book Generalized Linear Models for Insurance Data written by Piet de Jong and published by Cambridge University Press. This book was released on 2008-02-28 with total page 207 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is the only book actuaries need to understand generalized linear models (GLMs) for insurance applications. GLMs are used in the insurance industry to support critical decisions. Until now, no text has introduced GLMs in this context or addressed the problems specific to insurance data. Using insurance data sets, this practical, rigorous book treats GLMs, covers all standard exponential family distributions, extends the methodology to correlated data structures, and discusses recent developments which go beyond the GLM. The issues in the book are specific to insurance data, such as model selection in the presence of large data sets and the handling of varying exposure times. Exercises and data-based practicals help readers to consolidate their skills, with solutions and data sets given on the companion website. Although the book is package-independent, SAS code and output examples feature in an appendix and on the website. In addition, R code and output for all the examples are provided on the website.
Book Synopsis Spatial Uncertainty in Ecology by : Carolyn T. Hunsaker
Download or read book Spatial Uncertainty in Ecology written by Carolyn T. Hunsaker and published by Springer Science & Business Media. This book was released on 2013-12-01 with total page 417 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is one of the first books to take an ecological perspective on uncertainty in spatial data. It applies principles and techniques from geography and other disciplines to ecological research, and thus delivers the tools of cartography, cognition, spatial statistics, remote sensing and computer sciences by way of spatial data. After describing the uses of such data in ecological research, the authors discuss how to account for the effects of uncertainty in various methods of analysis.
Book Synopsis Healthcare Risk Adjustment and Predictive Modeling by : Ian G. Duncan
Download or read book Healthcare Risk Adjustment and Predictive Modeling written by Ian G. Duncan and published by ACTEX Publications. This book was released on 2011 with total page 350 pages. Available in PDF, EPUB and Kindle. Book excerpt: This text is listed on the Course of Reading for SOA Fellowship study in the Group & Health specialty track. Healthcare Risk Adjustment and Predictive Modeling provides a comprehensive guide to healthcare actuaries and other professionals interested in healthcare data analytics, risk adjustment and predictive modeling. The book first introduces the topic with discussions of health risk, available data, clinical identification algorithms for diagnostic grouping and the use of grouper models. The second part of the book presents the concept of data mining and some of the common approaches used by modelers. The third and final section covers a number of predictive modeling and risk adjustment case-studies, with examples from Medicaid, Medicare, disability, depression diagnosis and provider reimbursement, as well as the use of predictive modeling and risk adjustment outside the U.S. For readers who wish to experiment with their own models, the book also provides access to a test dataset.
Book Synopsis Predictive Modeling with SAS Enterprise Miner by : Kattamuri S. Sarma
Download or read book Predictive Modeling with SAS Enterprise Miner written by Kattamuri S. Sarma and published by SAS Institute. This book was released on 2017-07-20 with total page 574 pages. Available in PDF, EPUB and Kindle. Book excerpt: « Written for business analysts, data scientists, statisticians, students, predictive modelers, and data miners, this comprehensive text provides examples that will strengthen your understanding of the essential concepts and methods of predictive modeling. »--
Book Synopsis Modelling Mortality with Actuarial Applications by : Angus S. Macdonald
Download or read book Modelling Mortality with Actuarial Applications written by Angus S. Macdonald and published by Cambridge University Press. This book was released on 2018-05-03 with total page 387 pages. Available in PDF, EPUB and Kindle. Book excerpt: Modern mortality modelling for actuaries and actuarial students, with example R code, to unlock the potential of individual data.
Book Synopsis Statistical and Probabilistic Methods in Actuarial Science by : Philip J. Boland
Download or read book Statistical and Probabilistic Methods in Actuarial Science written by Philip J. Boland and published by CRC Press. This book was released on 2007-03-05 with total page 368 pages. Available in PDF, EPUB and Kindle. Book excerpt: Statistical and Probabilistic Methods in Actuarial Science covers many of the diverse methods in applied probability and statistics for students aspiring to careers in insurance, actuarial science, and finance. The book builds on students' existing knowledge of probability and statistics by establishing a solid and thorough understanding of
Book Synopsis Predictive Modeling Applications in Actuarial Science: Volume 1, Predictive Modeling Techniques by : Edward W. Frees
Download or read book Predictive Modeling Applications in Actuarial Science: Volume 1, Predictive Modeling Techniques written by Edward W. Frees and published by Cambridge University Press. This book was released on 2014-07-28 with total page 565 pages. Available in PDF, EPUB and Kindle. Book excerpt: Predictive modeling involves the use of data to forecast future events. It relies on capturing relationships between explanatory variables and the predicted variables from past occurrences and exploiting this to predict future outcomes. Forecasting future financial events is a core actuarial skill - actuaries routinely apply predictive-modeling techniques in insurance and other risk-management applications. This book is for actuaries and other financial analysts who are developing their expertise in statistics and wish to become familiar with concrete examples of predictive modeling. The book also addresses the needs of more seasoned practising analysts who would like an overview of advanced statistical topics that are particularly relevant in actuarial practice. Predictive Modeling Applications in Actuarial Science emphasizes lifelong learning by developing tools in an insurance context, providing the relevant actuarial applications, and introducing advanced statistical techniques that can be used by analysts to gain a competitive advantage in situations with complex data.
