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Bayesian Statistics in Actuarial Science

Bayesian Statistics in Actuarial Science
Author: Stuart A. Klugman
Publisher: Springer Science & Business Media
Total Pages: 242
Release: 2013-04-17
Genre: Business & Economics
ISBN: 9401708452

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The debate between the proponents of "classical" and "Bayesian" statistica} methods continues unabated. It is not the purpose of the text to resolve those issues but rather to demonstrate that within the realm of actuarial science there are a number of problems that are particularly suited for Bayesian analysis. This has been apparent to actuaries for a long time, but the lack of adequate computing power and appropriate algorithms had led to the use of various approximations. The two greatest advantages to the actuary of the Bayesian approach are that the method is independent of the model and that interval estimates are as easy to obtain as point estimates. The former attribute means that once one learns how to analyze one problem, the solution to similar, but more complex, problems will be no more difficult. The second one takes on added significance as the actuary of today is expected to provide evidence concerning the quality of any estimates. While the examples are all actuarial in nature, the methods discussed are applicable to any structured estimation problem. In particular, statisticians will recognize that the basic credibility problem has the same setting as the random effects model from analysis of variance.


Bayesian Statistics in Actuarial Science

Bayesian Statistics in Actuarial Science
Author: Jodi Lynn Palm
Publisher:
Total Pages: 104
Release: 1995
Genre: Bayesian statistical decision theory
ISBN:

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Statistical and Probabilistic Methods in Actuarial Science

Statistical and Probabilistic Methods in Actuarial Science
Author: Philip J. Boland
Publisher: CRC Press
Total Pages: 368
Release: 2007-03-05
Genre: Business & Economics
ISBN: 158488696X

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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


Applied Bayesian Statistics

Applied Bayesian Statistics
Author: Mary Kathryn Cowles
Publisher: Springer Science & Business Media
Total Pages: 238
Release: 2013-01-04
Genre: Mathematics
ISBN: 1461456967

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This book is based on over a dozen years teaching a Bayesian Statistics course. The material presented here has been used by students of different levels and disciplines, including advanced undergraduates studying Mathematics and Statistics and students in graduate programs in Statistics, Biostatistics, Engineering, Economics, Marketing, Pharmacy, and Psychology. The goal of the book is to impart the basics of designing and carrying out Bayesian analyses, and interpreting and communicating the results. In addition, readers will learn to use the predominant software for Bayesian model-fitting, R and OpenBUGS. The practical approach this book takes will help students of all levels to build understanding of the concepts and procedures required to answer real questions by performing Bayesian analysis of real data. Topics covered include comparing and contrasting Bayesian and classical methods, specifying hierarchical models, and assessing Markov chain Monte Carlo output. Kate Cowles taught Suzuki piano for many years before going to graduate school in Biostatistics. Her research areas are Bayesian and computational statistics, with application to environmental science. She is on the faculty of Statistics at The University of Iowa.


Statistical and Probabilistic Methods in Actuarial Science

Statistical and Probabilistic Methods in Actuarial Science
Author: Philip J. Boland
Publisher: CRC Press
Total Pages: 369
Release: 2007-03-05
Genre: Mathematics
ISBN: 1584886951

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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 these methods. It also emphasizes the wide variety of practical situations in insurance and actuarial science where these techniques may be used. Although some chapters are linked, several can be studied independently from the others. The first chapter introduces claims reserving via the deterministic chain ladder technique. The next few chapters survey loss distributions, risk models in a fixed period of time, and surplus processes, followed by an examination of credibility theory in which collateral and sample information are brought together to provide reasonable methods of estimation. In the subsequent chapter, experience rating via no claim discount schemes for motor insurance provides an interesting application of Markov chain methods. The final chapters discuss generalized linear models and decision and game theory. Developed by an author with many years of teaching experience, this text presents an accessible, sound foundation in both the theory and applications of actuarial science. It encourages students to use the statistical software package R to check examples and solve problems.


Actuarial Science

Actuarial Science
Author: I.B. MacNeill
Publisher: Springer Science & Business Media
Total Pages: 258
Release: 2012-12-06
Genre: Mathematics
ISBN: 9400947968

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On May 27-31, 1985, a series of symposia was held at The University of Western Ontario, London, Canada, to celebrate the 70th birthday of Pro fessor V. M. Joshi. These symposia were chosen to reflect Professor Joshi's research interests as well as areas of expertise in statistical science among faculty in the Departments of Statistical and Actuarial Sciences, Economics, Epidemiology and Biostatistics, and Philosophy. From these symposia, the six volumes which comprise the "Joshi Festschrift" have arisen. The 117 articles in this work reflect the broad interests and high quality of research of those who attended our conference. We would like to thank all of the contributors for their superb cooperation in helping us to complete this project. Our deepest gratitude must go to the three people who have spent so much of their time in the past year typing these volumes: Jackie Bell, Lise Constant, and Sandy Tarnowski. This work has been printed from "camera ready" copy produced by our Vax 785 computer and QMS Lasergraphix printers, using the text processing software TEX. At the initiation of this project, we were neophytes in the use of this system. Thank you, Jackie, Lise, and Sandy, for having the persistence and dedication needed to complete this undertaking.


Bayesian Claims Reserving Methods in Non-life Insurance with Stan

Bayesian Claims Reserving Methods in Non-life Insurance with Stan
Author: Guangyuan Gao
Publisher: Springer
Total Pages: 205
Release: 2018-12-31
Genre: Mathematics
ISBN: 9811336091

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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.


Predictive Modeling Applications in Actuarial Science

Predictive Modeling Applications in Actuarial Science
Author: Edward W. Frees
Publisher: Cambridge University Press
Total Pages: 565
Release: 2014-07-28
Genre: Business & Economics
ISBN: 1107029872

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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.


Probability and Statistics for Actuaries

Probability and Statistics for Actuaries
Author: Natalia A. Humphreys
Publisher: Cognella Academic Publishing
Total Pages:
Release: 2021-04-07
Genre:
ISBN: 9781793552792

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Probability and Statistics for Actuaries provides students with a structured and detailed explanation of the probabilistic and statistical aspects of actuarial science to help them formalize and deepen their knowledge in these areas. The text is divided into two distinct parts with the first focusing on probability and the second focusing on statistics. Part I begins with a strategic review of probabilistic models and techniques. Additional chapters cover conditional probability, variance, and expectation with distinct emphasis of the Bayesian approach. Students learn about the Bayesian framework for credibility and the relationship between Bühlmann approximation and empirical Bayes. Part II begins with a review of statistical models and techniques and then proceeds with a robust chapter that discusses parametric statistical inference. The text includes two helpful appendices: a one-sample K-S table and a one-sample A-D table. Designed to help students expand their knowledge, Probability and Statistics for Actuaries is an exceptional resource for courses within the actuarial sciences. It is also ideal for individuals preparing to take professional exams given by the Society of Actuaries and Casualty Actuarial Society.


Computational Actuarial Science with R

Computational Actuarial Science with R
Author: Arthur Charpentier
Publisher: CRC Press
Total Pages: 652
Release: 2014-08-26
Genre: Business & Economics
ISBN: 1466592591

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A Hands-On Approach to Understanding and Using Actuarial Models Computational 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/C++ embedded codes. After an introduction to the R language, the book is divided into four parts. The first one addresses methodology and statistical modeling issues. The second part discusses the computational facets of life insurance, including life contingencies calculations and prospective life tables. Focusing on finance from an actuarial perspective, the next part presents techniques for modeling stock prices, nonlinear time series, yield curves, interest rates, and portfolio optimization. The last part explains how to use R to deal with computational issues of nonlife insurance. Taking a do-it-yourself approach to understanding algorithms, this book demystifies the computational aspects of actuarial science. It shows that even complex computations can usually be done without too much trouble. Datasets used in the text are available in an R package (CASdatasets).