Effective statistical learning methods for actuaries ii, Denuit, Michel Hainaut, Donatien Trufin, Julien
Автор: Michel Denuit; Donatien Hainaut; Julien Trufin Название: Effective Statistical Learning Methods for Actuaries III ISBN: 3030258262 ISBN-13(EAN): 9783030258269 Издательство: Springer Рейтинг: Цена: 6986.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: 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.
Автор: Chan Wai-Sum Et Al Название: Financial mathematics for actuaries (second edition) ISBN: 9813224673 ISBN-13(EAN): 9789813224674 Издательство: World Scientific Publishing Рейтинг: Цена: 6336.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Financial Mathematics for Actuaries is a textbook for students in actuarial science, quantitative finance, financial engineering and quantitative risk management and is designed for a one-semester undergraduate course.Covering the theories of interest rates, with applications to the evaluation of cash flows, the pricing of fixed income securities and the management of bonds, this textbook also contains numerous examples and exercises and extensive coverage of various Excel functions for financial calculation. Discussions are linked to real financial market data, such as historical term structure, and traded financial securities.The topics discussed in this book are essential for actuarial science students. They are also useful for students in financial markets, investments and quantitative finance. Students preparing for examinations in financial mathematics with various professional actuarial bodies will also find this book useful for self-study.In this second edition, the recent additions in the learning objectives of the Society of Actuaries Exam FM have been covered.
Автор: Washington, Simon Mannering, Fred (university Of S Название: Statistical and econometric methods for transportation data analysis ISBN: 0367199025 ISBN-13(EAN): 9780367199029 Издательство: Taylor&Francis Рейтинг: Цена: 17609.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Describing tools commonly used in the field, this textbook provides an understanding of a broad range of analytical tools required to solve transportation problems. It includes a wide breadth of examples and case studies in various aspects of transportation planning, engineering, safety, and economics.
Автор: Matange Sanjay, Heath Dan, Sas Institute Название: Statistical Graphics Procedures by Example: Effective Graphs Using SAS ISBN: 1607647621 ISBN-13(EAN): 9781607647621 Издательство: Неизвестно Рейтинг: Цена: 12865.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Автор: Michel Denuit; Donatien Hainaut; Julien Trufin Название: Effective Statistical Learning Methods for Actuaries I ISBN: 303025819X ISBN-13(EAN): 9783030258191 Издательство: Springer Рейтинг: Цена: 6288.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: 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). Going beyond mean modeling, it considers volatility modeling (double GLMs) and the general modeling of location, scale and shape parameters (GAMLSS).
Автор: Tse Yiu-Kuen Название: Financial Mathematics For Actuaries ISBN: 9813224665 ISBN-13(EAN): 9789813224667 Издательство: World Scientific Publishing Рейтинг: Цена: 19166.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Financial Mathematics for Actuaries is a textbook for students in actuarial science, quantitative finance, financial engineering and quantitative risk management and is designed for a one-semester undergraduate course.Covering the theories of interest rates, with applications to the evaluation of cash flows, the pricing of fixed income securities and the management of bonds, this textbook also contains numerous examples and exercises and extensive coverage of various Excel functions for financial calculation. Discussions are linked to real financial market data, such as historical term structure, and traded financial securities.The topics discussed in this book are essential for actuarial science students. They are also useful for students in financial markets, investments and quantitative finance. Students preparing for examinations in financial mathematics with various professional actuarial bodies will also find this book useful for self-study.In this second edition, the recent additions in the learning objectives of the Society of Actuaries Exam FM have been covered.
Описание: The purpose of this book is to provide an accessible, yet comprehensive, account of data science and machine learning. It is intended for anyone interested in gaining a better understanding of the mathematics and statistics that underpin the rich variety of ideas and machine learning algorithms in data science.
Описание: An examination of system reliability theory, this title features in-depth discussion of dependability management and reliability centered systems as well as functional safety issues-matters critical to the IEC standards.
Автор: Norou Diawara Название: Modern Statistical Methods for Spatial and Multivariate Data ISBN: 3030114309 ISBN-13(EAN): 9783030114305 Издательство: Springer Рейтинг: Цена: 11878.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
This contributed volume features invited papers on current models and statistical methods for spatial and multivariate data. With a focus on recent advances in statistics, topics include spatio-temporal aspects, classification techniques, the multivariate outcomes with zero and doubly-inflated data, discrete choice modelling, copula distributions, and feasible algorithmic solutions. Special emphasis is placed on applications such as the use of spatial and spatio-temporal models for rainfall in South Carolina and the multivariate sparse areal mixed model for the Census dataset for the state of Iowa. Articles use simulated and aggregated data examples to show the flexibility and wide applications of proposed techniques.
Carefully peer-reviewed and pedagogically presented for a broad readership, this volume is suitable for graduate and postdoctoral students interested in interdisciplinary research. Researchers in applied statistics and sciences will find this book an important resource on the latest developments in the field. In keeping with the STEAM-H series, the editors hope to inspire interdisciplinary understanding and collaboration.
Автор: Marco Corazza; Cira Perna; Marilena Sibillo; Flore Название: Mathematical and Statistical Methods for Actuarial Sciences and Finance ISBN: 3319502336 ISBN-13(EAN): 9783319502335 Издательство: Springer Рейтинг: Цена: 13974.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This volume gathers selected peer-reviewed papers presented at the "International MAF Conference 2016 - Mathematical and Statistical Methods for Actuarial Sciences and Finance" held in Paris at the University of Paris-Dauphine from March 30 to April 1, 2016.
Автор: Manly Bryan F.J. Название: Multivariate Statistical Methods ISBN: 1498728960 ISBN-13(EAN): 9781498728966 Издательство: Taylor&Francis Рейтинг: Цена: 8726.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
Multivariate Statistical Methods: A Primer provides an introductory overview of multivariate methods without getting too deep into the mathematical details. This fourth edition is a revised and updated version of this bestselling introductory textbook. It retains the clear and concise style of the previous editions of the book and focuses on examples from biological and environmental sciences. The major update with this edition is that R code has been included for each of the analyses described, although in practice any standard statistical package can be used.
The original idea with this book still applies. This was to make it as short as possible and enable readers to begin using multivariate methods in an intelligent manner. With updated information on multivariate analyses, new references, and R code included, this book continues to provide a timely introduction to useful tools for multivariate statistical analysis.
Due to the scale and complexity of data sets currently being collected in areas such as health, transportation, environmental science, engineering, information technology, business and finance, modern quantitative analysts are seeking improved and appropriate computational and statistical methods to explore, model and draw inferences from big data. This book aims to introduce suitable approaches for such endeavours, providing applications and case studies for the purpose of demonstration.
"Computational and Statistical Methods for Analysing Big Data with Applications" starts with an overview of the era of big data. It then goes onto explain the computational and statistical methods which have been commonly applied in the big data revolution. For each of these methods, an example is provided as a guide to its application. Five case studies are presented next, focusing on computer vision with massive training data, spatial data analysis, advanced experimental design methods for big data, big data in clinical medicine, and analysing data collected from mobile devices, respectively. The book concludes with some final thoughts and suggested areas for future research in big data.
Advanced computational and statistical methodologies for analysing big data are developed.
Experimental design methodologies are described and implemented to make the analysis of big data more computationally tractable.
Case studies are discussed to demonstrate the implementation of the developed methods.
Five high-impact areas of application are studied: computer vision, geosciences, commerce, healthcare and transportation.
Computing code/programs are provided where appropriate.
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