R Programming For Actuarial Science

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R Programming For Actuarial Science

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Author : Peter McQuire
language : en
Publisher: John Wiley & Sons
Release Date : 2023-10-26

R Programming For Actuarial Science written by Peter McQuire and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-10-26 with Computers categories.

R Programming for Actuarial Science Professional resource providing an introduction to R coding for actuarial and financial mathematics applications, with real-life examples R Programming for Actuarial Science provides a grounding in R programming applied to the mathematical and statistical methods that are of relevance for actuarial work. In R Programming for Actuarial Science, readers will find: Basic theory for each chapter to complement other actuarial textbooks which provide foundational theory in depth. Topics covered include compound interest, statistical inference, asset-liability matching, time series, loss distributions, contingencies, mortality models, and option pricing plus many more typically covered in university courses. More than 400 coding examples and exercises, most with solutions, to enable students to gain a better understanding of underlying mathematical and statistical principles. An overall basic to intermediate level of coverage in respect of numerous actuarial applications, and real-life examples included with every topic. Providing a highly useful combination of practical discussion and basic theory, R Programming for Actuarial Science is an essential reference for BSc/MSc students in actuarial science, trainee actuaries studying privately, and qualified actuaries with little programming experience, along with undergraduate students studying finance, business, and economics.

Actuarial Science

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Author : Hanji Shang
language : en
Publisher: World Scientific
Release Date : 2006

Actuarial Science written by Hanji Shang and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006 with Mathematics categories.

Since actuarial education was introduced into China in the 1980s, Chinese scholars have paid greater attention to the theoretical research of actuarial science. Professors and industry experts from well-known universities in China recently worked together on the project ?Insurance Information Processing and Actuarial Mathematics Theory and Methodology?, which was supported by the Chinese government. Summarizing what they achieved, this volume provides a study of some basic problems of actuarial science, including risk models, risk evaluation and analysis, and premium principles. The contributions cover some new applications of probability and statistics, fuzzy mathematics and financial economics to the field of actuarial practices. Discussions on the new insurance market in China are also presented.

Effective Statistical Learning Methods For Actuaries Ii

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Author : Michel Denuit
language : en
Publisher: Springer
Release Date : 2020-11-17

Effective Statistical Learning Methods For Actuaries Ii written by Michel Denuit and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-11-17 with Business & Economics categories.

This book summarizes the state of the art in tree-based methods for insurance: regression trees, random forests and boosting methods. It also exhibits the tools which make it possible to assess the predictive performance of tree-based models. Actuaries need these advanced analytical tools to turn the massive data sets now at their disposal into opportunities. The exposition alternates between methodological aspects and numerical illustrations or case studies. All numerical illustrations are performed with the R statistical software. The technical prerequisites are kept at a reasonable level in order to reach a broad readership. In particular, master's students in actuarial sciences and actuaries wishing to update their skills in machine learning will find the book useful. This is the second of three volumes entitled Effective Statistical Learning Methods for Actuaries. Written by actuaries for actuaries, this series offers a comprehensive overview of insurance data analytics with applications to P&C, life and health insurance.

Modern Actuarial Risk Theory

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Author : Rob Kaas
language : en
Publisher: Springer Science & Business Media
Release Date : 2008-12-03

Modern Actuarial Risk Theory written by Rob Kaas 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 2008-12-03 with Business & Economics categories.

Modern Actuarial Risk Theory contains what every actuary needs to know about non-life insurance mathematics. It starts with the standard material like utility theory, individual and collective model and basic ruin theory. Other topics are risk measures and premium principles, bonus-malus systems, ordering of risks and credibility theory. It also contains some chapters about Generalized Linear Models, applied to rating and IBNR problems. As to the level of the mathematics, the book would fit in a bachelors or masters program in quantitative economics or mathematical statistics. This second and.

R For Everyone

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Author : Jared P. Lander
language : en
Publisher: Addison-Wesley Professional
Release Date : 2017-06-13

R For Everyone written by Jared P. Lander and has been published by Addison-Wesley Professional this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-06-13 with Computers categories.

Statistical Computation for Programmers, Scientists, Quants, Excel Users, and Other Professionals Using the open source R language, you can build powerful statistical models to answer many of your most challenging questions. R has traditionally been difficult for non-statisticians to learn, and most R books assume far too much knowledge to be of help. R for Everyone, Second Edition, is the solution. Drawing on his unsurpassed experience teaching new users, professional data scientist Jared P. Lander has written the perfect tutorial for anyone new to statistical programming and modeling. Organized to make learning easy and intuitive, this guide focuses on the 20 percent of R functionality you’ll need to accomplish 80 percent of modern data tasks. Lander’s self-contained chapters start with the absolute basics, offering extensive hands-on practice and sample code. You’ll download and install R; navigate and use the R environment; master basic program control, data import, manipulation, and visualization; and walk through several essential tests. Then, building on this foundation, you’ll construct several complete models, both linear and nonlinear, and use some data mining techniques. After all this you’ll make your code reproducible with LaTeX, RMarkdown, and Shiny. By the time you’re done, you won’t just know how to write R programs, you’ll be ready to tackle the statistical problems you care about most. Coverage includes Explore R, RStudio, and R packages Use R for math: variable types, vectors, calling functions, and more Exploit data structures, including data.frames, matrices, and lists Read many different types of data Create attractive, intuitive statistical graphics Write user-defined functions Control program flow with if, ifelse, and complex checks Improve program efficiency with group manipulations Combine and reshape multiple datasets Manipulate strings using R’s facilities and regular expressions Create normal, binomial, and Poisson probability distributions Build linear, generalized linear, and nonlinear models Program basic statistics: mean, standard deviation, and t-tests Train machine learning models Assess the quality of models and variable selection Prevent overfitting and perform variable selection, using the Elastic Net and Bayesian methods Analyze univariate and multivariate time series data Group data via K-means and hierarchical clustering Prepare reports, slideshows, and web pages with knitr Display interactive data with RMarkdown and htmlwidgets Implement dashboards with Shiny Build reusable R packages with devtools and Rcpp Register your product at informit.com/register for convenient access to downloads, updates, and corrections as they become available.

Solutions Manual For Actuarial Mathematics For Life Contingent Risks

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Author : David C. M. Dickson
language : en
Publisher: Cambridge University Press
Release Date : 2012-03-26

Solutions Manual For Actuarial Mathematics For Life Contingent Risks written by David C. M. Dickson and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-03-26 with Business & Economics categories.

"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.

Regression Modeling With Actuarial And Financial Applications

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Author : Edward W. Frees
language : en
Publisher: Cambridge University Press
Release Date : 2010

Regression Modeling With Actuarial And Financial Applications written by Edward W. Frees and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010 with Business & Economics categories.

This book teaches multiple regression and time series and how to use these to analyze real data in risk management and finance.

Time Series Analysis

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Author : Jonathan D. Cryer
language : en
Publisher: Springer Science & Business Media
Release Date : 2008-03-06

Time Series Analysis written by Jonathan D. Cryer 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 2008-03-06 with Mathematics categories.

This book has been developed for a one-semester course usually attended by students in statistics, economics, business, engineering, and quantitative social sciences. A unique feature of this edition is its integration with the R computing environment. Basic applied statistics is assumed through multiple regression. Calculus is assumed only to the extent of minimizing sums of squares but a calculus-based introduction to statistics is necessary for a thorough understanding of some of the theory. Actual time series data drawn from various disciplines are used throughout the book to illustrate the methodology.

Financial Analytics With R

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Author : Mark J. Bennett
language : en
Publisher: Cambridge University Press
Release Date : 2016-10-06

Financial Analytics With R written by Mark J. Bennett and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-10-06 with Business & Economics categories.

Financial Analytics with R sharpens readers' skills in time-series, forecasting, portfolio selection, covariance clustering, prediction, and derivative securities.

Actuarial Statistics

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Author : Shailaja R. Deshmukh
language : en
Publisher:
Release Date : 2009

Actuarial Statistics written by Shailaja R. Deshmukh and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009 with Actuarial science categories.