Effective Statistical Learning Methods for Actuaries II

Download Effective Statistical Learning Methods for Actuaries II PDF Online Free

Author :
Publisher : Springer Nature
ISBN 13 : 303057556X
Total Pages : 228 pages
Book Rating : 4.64/5 ( download)

DOWNLOAD NOW!


Book Synopsis Effective Statistical Learning Methods for Actuaries II by : Michel Denuit

Download or read book Effective Statistical Learning Methods for Actuaries II written by Michel Denuit and published by Springer Nature. This book was released on 2020-11-16 with total page 228 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Effective Statistical Learning Methods for Actuaries I

Download Effective Statistical Learning Methods for Actuaries I PDF Online Free

Author :
Publisher : Springer Nature
ISBN 13 : 3030258203
Total Pages : 441 pages
Book Rating : 4.07/5 ( download)

DOWNLOAD NOW!


Book Synopsis Effective Statistical Learning Methods for Actuaries I by : Michel Denuit

Download or read book Effective Statistical Learning Methods for Actuaries I written by Michel Denuit and published by Springer Nature. This book was released on 2019-09-03 with total page 441 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book summarizes the state of the art in generalized linear models (GLMs) and their various extensions: GAMs, mixed models and credibility, and some nonlinear variants (GNMs). In order to deal with tail events, analytical tools from Extreme Value Theory are presented. Going beyond mean modeling, it considers volatility modeling (double GLMs) and the general modeling of location, scale and shape parameters (GAMLSS). 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 case studies, providing numerical illustrations using the R statistical software. The technical prerequisites are kept at a reasonable level in order to reach a broad readership. This is the first 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. Although closely related to the other two volumes, this volume can be read independently.

Effective Statistical Learning Methods for Actuaries III

Download Effective Statistical Learning Methods for Actuaries III PDF Online Free

Author :
Publisher : Springer Nature
ISBN 13 : 3030258270
Total Pages : 250 pages
Book Rating : 4.76/5 ( download)

DOWNLOAD NOW!


Book Synopsis Effective Statistical Learning Methods for Actuaries III by : Michel Denuit

Download or read book Effective Statistical Learning Methods for Actuaries III written by Michel Denuit and published by Springer Nature. This book was released on 2019-10-31 with total page 250 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book reviews some of the most recent developments in neural networks, with a focus on applications in actuarial sciences and finance. It simultaneously introduces the relevant tools for developing and analyzing neural networks, in a style that is mathematically rigorous yet accessible. Artificial intelligence and neural networks offer a powerful alternative to statistical methods for analyzing data. Various topics are covered from feed-forward networks to deep learning, such as Bayesian learning, boosting methods and Long Short Term Memory models. All methods are applied to claims, mortality or time-series forecasting. Requiring only a basic knowledge of statistics, this book is written for masters students in the actuarial sciences and for actuaries wishing to update their skills in machine learning. This is the third 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. Although closely related to the other two volumes, this volume can be read independently.

Effective Statistical Learning Methods for Actuaries I

Download Effective Statistical Learning Methods for Actuaries I PDF Online Free

Author :
Publisher :
ISBN 13 : 9783030258214
Total Pages : 441 pages
Book Rating : 4.11/5 ( download)

DOWNLOAD NOW!


Book Synopsis Effective Statistical Learning Methods for Actuaries I by : Michel Denuit

Download or read book Effective Statistical Learning Methods for Actuaries I written by Michel Denuit and published by . This book was released on 2019 with total page 441 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book summarizes the state of the art in generalized linear models (GLMs) and their various extensions: GAMs, mixed models and credibility, and some nonlinear variants (GNMs). In order to deal with tail events, analytical tools from Extreme Value Theory are presented. Going beyond mean modeling, it considers volatility modeling (double GLMs) and the general modeling of location, scale and shape parameters (GAMLSS). 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 case studies, providing numerical illustrations using the R statistical software. The technical prerequisites are kept at a reasonable level in order to reach a broad readership. This is the first 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. Although closely related to the other two volumes, this volume can be read independently.

Effective Statistical Learning Methods for Actuaries

Download Effective Statistical Learning Methods for Actuaries PDF Online Free

Author :
Publisher :
ISBN 13 : 9783030258283
Total Pages : pages
Book Rating : 4.89/5 ( download)

DOWNLOAD NOW!


Book Synopsis Effective Statistical Learning Methods for Actuaries by : Michel Denuit

Download or read book Effective Statistical Learning Methods for Actuaries written by Michel Denuit and published by . This book was released on 2019 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Artificial intelligence and neural networks offer a powerful alternative to statistical methods for analyzing data. This book reviews some of the most recent developments in neural networks, with a focus on applications in actuarial sciences and finance. The third volume of the trilogy simultaneously introduces the relevant tools for developing and analyzing neural networks, in a style that is mathematically rigorous and yet accessible. The authors proceed by successive generalizations, requiring of the reader only a basic knowledge of statistics. Various topics are covered from feed-forward networks to deep learning, such as Bayesian learning, boosting methods and Long Short Term Memory models. All methods are applied to claims, mortality or time-series forecasting. This book is written for masters students in the actuarial sciences and for actuaries wishing to update their skills in machine learning.

Statistical Foundations of Actuarial Learning and its Applications

Download Statistical Foundations of Actuarial Learning and its Applications PDF Online Free

Author :
Publisher : Springer Nature
ISBN 13 : 303112409X
Total Pages : 611 pages
Book Rating : 4.99/5 ( download)

DOWNLOAD NOW!


Book Synopsis Statistical Foundations of Actuarial Learning and its Applications by : Mario V. Wüthrich

Download or read book Statistical Foundations of Actuarial Learning and its Applications written by Mario V. Wüthrich and published by Springer Nature. This book was released on 2022-11-22 with total page 611 pages. Available in PDF, EPUB and Kindle. Book excerpt: This open access book discusses the statistical modeling of insurance problems, a process which comprises data collection, data analysis and statistical model building to forecast insured events that may happen in the future. It presents the mathematical foundations behind these fundamental statistical concepts and how they can be applied in daily actuarial practice. Statistical modeling has a wide range of applications, and, depending on the application, the theoretical aspects may be weighted differently: here the main focus is on prediction rather than explanation. Starting with a presentation of state-of-the-art actuarial models, such as generalized linear models, the book then dives into modern machine learning tools such as neural networks and text recognition to improve predictive modeling with complex features. Providing practitioners with detailed guidance on how to apply machine learning methods to real-world data sets, and how to interpret the results without losing sight of the mathematical assumptions on which these methods are based, the book can serve as a modern basis for an actuarial education syllabus.

Insurance, Biases, Discrimination and Fairness

Download Insurance, Biases, Discrimination and Fairness PDF Online Free

Author :
Publisher : Springer Nature
ISBN 13 : 303149783X
Total Pages : 491 pages
Book Rating : 4.34/5 ( download)

DOWNLOAD NOW!


Book Synopsis Insurance, Biases, Discrimination and Fairness by : Arthur Charpentier

Download or read book Insurance, Biases, Discrimination and Fairness written by Arthur Charpentier and published by Springer Nature. This book was released on with total page 491 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Statistical and Probabilistic Methods in Actuarial Science

Download Statistical and Probabilistic Methods in Actuarial Science PDF Online Free

Author :
Publisher : CRC Press
ISBN 13 : 158488696X
Total Pages : 368 pages
Book Rating : 4.69/5 ( download)

DOWNLOAD NOW!


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

Mathematical and Statistical Methods for Actuarial Sciences and Finance

Download Mathematical and Statistical Methods for Actuarial Sciences and Finance PDF Online Free

Author :
Publisher : Springer Nature
ISBN 13 : 3030789659
Total Pages : 389 pages
Book Rating : 4.57/5 ( download)

DOWNLOAD NOW!


Book Synopsis Mathematical and Statistical Methods for Actuarial Sciences and Finance by : Marco Corazza

Download or read book Mathematical and Statistical Methods for Actuarial Sciences and Finance written by Marco Corazza and published by Springer Nature. This book was released on 2021-12-13 with total page 389 pages. Available in PDF, EPUB and Kindle. Book excerpt: The cooperation and contamination between mathematicians, statisticians and econometricians working in actuarial sciences and finance is improving the research on these topics and producing numerous meaningful scientific results. This volume presents new ideas, in the form of four- to six-page papers, presented at the International Conference eMAF2020 – Mathematical and Statistical Methods for Actuarial Sciences and Finance. Due to the now sadly famous COVID-19 pandemic, the conference was held remotely through the Zoom platform offered by the Department of Economics of the Ca’ Foscari University of Venice on September 18, 22 and 25, 2020. eMAF2020 is the ninth edition of an international biennial series of scientific meetings, started in 2004 at the initiative of the Department of Economics and Statistics of the University of Salerno. The effectiveness of this idea has been proven by wide participation in all editions, which have been held in Salerno (2004, 2006, 2010 and 2014), Venice (2008, 2012 and 2020), Paris (2016) and Madrid (2018). This book covers a wide variety of subjects: artificial intelligence and machine learning in finance and insurance, behavioral finance, credit risk methods and models, dynamic optimization in finance, financial data analytics, forecasting dynamics of actuarial and financial phenomena, foreign exchange markets, insurance models, interest rate models, longevity risk, models and methods for financial time series analysis, multivariate techniques for financial markets analysis, pension systems, portfolio selection and management, real-world finance, risk analysis and management, trading systems, and others. This volume is a valuable resource for academics, PhD students, practitioners, professionals and researchers. Moreover, it is also of interest to other readers with quantitative background knowledge.

Regression Modeling with Actuarial and Financial Applications

Download Regression Modeling with Actuarial and Financial Applications PDF Online Free

Author :
Publisher : Cambridge University Press
ISBN 13 : 0521760119
Total Pages : 585 pages
Book Rating : 4.19/5 ( download)

DOWNLOAD NOW!


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.