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Using The Odp Bootstrap Model
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Book Synopsis Using the ODP Bootstrap Model by : Mark R. Shapland
Download or read book Using the ODP Bootstrap Model written by Mark R. Shapland and published by . This book was released on 2016 with total page 116 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Bootstrap Methods by : Gerhard Dikta
Download or read book Bootstrap Methods written by Gerhard Dikta and published by Springer Nature. This book was released on 2021-08-10 with total page 256 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a compact introduction to the bootstrap method. In addition to classical results on point estimation and test theory, multivariate linear regression models and generalized linear models are covered in detail. Special attention is given to the use of bootstrap procedures to perform goodness-of-fit tests to validate model or distributional assumptions. In some cases, new methods are presented here for the first time. The text is motivated by practical examples and the implementations of the corresponding algorithms are always given directly in R in a comprehensible form. Overall, R is given great importance throughout. Each chapter includes a section of exercises and, for the more mathematically inclined readers, concludes with rigorous proofs. The intended audience is graduate students who already have a prior knowledge of probability theory and mathematical statistics.
Book Synopsis Claims Reserving in General Insurance by : David Hindley
Download or read book Claims Reserving in General Insurance written by David Hindley and published by Cambridge University Press. This book was released on 2017-10-26 with total page 514 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is a comprehensive and accessible reference source that documents the theoretical and practical aspects of all the key deterministic and stochastic reserving methods that have been developed for use in general insurance. Worked examples and mathematical details are included, along with many of the broader topics associated with reserving in practice. The key features of reserving in a range of different contexts in the UK and elsewhere are also covered. The book contains material that will appeal to anyone with an interest in claims reserving. It can be used as a learning resource for actuarial students who are studying the relevant parts of their professional bodies' examinations, as well as by others who are new to the subject. More experienced insurance and other professionals can use the book to refresh or expand their knowledge in any of the wide range of reserving topics covered in the book.
Book Synopsis Bootstrap Model Selection Via the Cost Complexity Parameter in Regression by : J. Sunil Rao
Download or read book Bootstrap Model Selection Via the Cost Complexity Parameter in Regression written by J. Sunil Rao and published by . This book was released on 1993 with total page 15 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Bootstrap Methods and Their Application by : A. C. Davison
Download or read book Bootstrap Methods and Their Application written by A. C. Davison and published by Cambridge University Press. This book was released on 1997-10-28 with total page 606 pages. Available in PDF, EPUB and Kindle. Book excerpt: Disk contains the library functions and documentation for use with Splus for Windows.
Download or read book Claim Models written by Greg Taylor and published by MDPI. This book was released on 2020-04-15 with total page 108 pages. Available in PDF, EPUB and Kindle. Book excerpt: This collection of articles addresses the most modern forms of loss reserving methodology: granular models and machine learning models. New methodologies come with questions about their applicability. These questions are discussed in one article, which focuses on the relative merits of granular and machine learning models. Others illustrate applications with real-world data. The examples include neural networks, which, though well known in some disciplines, have previously been limited in the actuarial literature. This volume expands on that literature, with specific attention to their application to loss reserving. For example, one of the articles introduces the application of neural networks of the gated recurrent unit form to the actuarial literature, whereas another uses a penalized neural network. Neural networks are not the only form of machine learning, and two other papers outline applications of gradient boosting and regression trees respectively. Both articles construct loss reserves at the individual claim level so that these models resemble granular models. One of these articles provides a practical application of the model to claim watching, the action of monitoring claim development and anticipating major features. Such watching can be used as an early warning system or for other administrative purposes. Overall, this volume is an extremely useful addition to the libraries of those working at the loss reserving frontier.
Book Synopsis Bayesian Claims Reserving Methods in Non-life Insurance with Stan by : Guangyuan Gao
Download or read book Bayesian Claims Reserving Methods in Non-life Insurance with Stan written by Guangyuan Gao and published by Springer. This book was released on 2018-12-31 with total page 205 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book first provides a review of various aspects of Bayesian statistics. It then investigates three types of claims reserving models in the Bayesian framework: chain ladder models, basis expansion models involving a tail factor, and multivariate copula models. For the Bayesian inferential methods, this book largely relies on Stan, a specialized software environment which applies Hamiltonian Monte Carlo method and variational Bayes.
Book Synopsis Bootstrapping and Related Techniques by : Karl-Heinz Jöckel
Download or read book Bootstrapping and Related Techniques written by Karl-Heinz Jöckel and published by Springer. This book was released on 1992 with total page 264 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Bootstrap Model Averaging Unit Root Inference by : Bruce Hansen
Download or read book Bootstrap Model Averaging Unit Root Inference written by Bruce Hansen and published by . This book was released on 2018 with total page 21 pages. Available in PDF, EPUB and Kindle. Book excerpt: Classical unit root tests are known to suffer from potentially crippling size distortions, and a range of procedures have been proposed to attenuate this problem, including the use of bootstrap procedures. It is also known that the estimating equation's functional form can affect the outcome of the test, and various model selection procedures have been proposed to overcome this limitation. In this paper, we adopt a model averaging procedure to deal with model uncertainty at the testing stage. In addition, we leverage an automatic model-free dependent bootstrap procedure where the null is imposed by simple differencing (the block length is automatically determined using recent developments for bootstrapping dependent processes). Monte Carlo simulations indicate that this approach exhibits the lowest size distortions among its peers in settings that confound existing approaches, while it has superior power relative to those peers whose size distortions do not preclude their general use. The proposed approach is fully automatic, and there are no nuisance parameters that have to be set by the user, which ought to appeal to practitioners.
Book Synopsis Stochastic Loss Reserving Using Generalized Linear Models by : Greg Taylor
Download or read book Stochastic Loss Reserving Using Generalized Linear Models written by Greg Taylor and published by . This book was released on 2016-05-04 with total page 100 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this monograph, authors Greg Taylor and Gráinne McGuire discuss generalized linear models (GLM) for loss reserving, beginning with strong emphasis on the chain ladder. The chain ladder is formulated in a GLM context, as is the statistical distribution of the loss reserve. This structure is then used to test the need for departure from the chain ladder model and to consider natural extensions of the chain ladder model that lend themselves to the GLM framework.
Book Synopsis Computational Actuarial Science with R by : Arthur Charpentier
Download or read book Computational Actuarial Science with R written by Arthur Charpentier and published by CRC Press. This book was released on 2014-08-26 with total page 638 pages. Available in PDF, EPUB and Kindle. Book excerpt: A Hands-On Approach to Understanding and Using Actuarial ModelsComputational Actuarial Science with R provides an introduction to the computational aspects of actuarial science. Using simple R code, the book helps you understand the algorithms involved in actuarial computations. It also covers more advanced topics, such as parallel computing and C/
Book Synopsis Adaptive Multimedia Retrieval: Identifying, Summarizing, and Recommending Image and Music by : Marcin Detyniecki
Download or read book Adaptive Multimedia Retrieval: Identifying, Summarizing, and Recommending Image and Music written by Marcin Detyniecki and published by Springer Science & Business Media. This book was released on 2010-08-05 with total page 194 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume constitutes the refereed proceedings of the 6th International Workshop on Adaptive Multimedia Retrieval, AMR 2008, held in Berlin, Germany, in June 2008.
Book Synopsis Bootstrapping by : Christopher Z. Mooney
Download or read book Bootstrapping written by Christopher Z. Mooney and published by SAGE. This book was released on 1993-08-09 with total page 84 pages. Available in PDF, EPUB and Kindle. Book excerpt: "This book is. . . clear and well-written. . . anyone with any interest in the basis of quantitative analysis simply must read this book. . . . well-written, with a wealth of explanation. . ." --Dougal Hutchison in Educational Research Using real data examples, this volume shows how to apply bootstrapping when the underlying sampling distribution of a statistic cannot be assumed normal, as well as when the sampling distribution has no analytic solution. In addition, it discusses the advantages and limitations of four bootstrap confidence interval methods--normal approximation, percentile, bias-corrected percentile, and percentile-t. The book concludes with a convenient summary of how to apply this computer-intensive methodology using various available software packages.
Book Synopsis The Statistical Bootstrap Model by : Christopher John Hamer
Download or read book The Statistical Bootstrap Model written by Christopher John Hamer and published by . This book was released on 1972 with total page 278 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Claims Reserving in General Insurance by : David Hindley
Download or read book Claims Reserving in General Insurance written by David Hindley and published by Cambridge University Press. This book was released on 2017-10-26 with total page 513 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is a single comprehensive reference source covering the key material on this subject, and describing both theoretical and practical aspects.
Book Synopsis Generalized Linear Models for Insurance Rating by : Mark Goldburd
Download or read book Generalized Linear Models for Insurance Rating written by Mark Goldburd and published by . This book was released on 2016-06-08 with total page 106 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Climate Time Series Analysis by : Manfred Mudelsee
Download or read book Climate Time Series Analysis written by Manfred Mudelsee and published by Springer Science & Business Media. This book was released on 2010-08-26 with total page 497 pages. Available in PDF, EPUB and Kindle. Book excerpt: Climate is a paradigm of a complex system. Analysing climate data is an exciting challenge, which is increased by non-normal distributional shape, serial dependence, uneven spacing and timescale uncertainties. This book presents bootstrap resampling as a computing-intensive method able to meet the challenge. It shows the bootstrap to perform reliably in the most important statistical estimation techniques: regression, spectral analysis, extreme values and correlation. This book is written for climatologists and applied statisticians. It explains step by step the bootstrap algorithms (including novel adaptions) and methods for confidence interval construction. It tests the accuracy of the algorithms by means of Monte Carlo experiments. It analyses a large array of climate time series, giving a detailed account on the data and the associated climatological questions. This makes the book self-contained for graduate students and researchers.