Statistical Inference in Financial and Insurance Mathematics with R

Statistical Inference in Financial and Insurance Mathematics with R
Author :
Publisher : Elsevier
Total Pages : 204
Release :
ISBN-10 : 9780081012611
ISBN-13 : 0081012616
Rating : 4/5 (11 Downloads)

Book Synopsis Statistical Inference in Financial and Insurance Mathematics with R by : Alexandre Brouste

Download or read book Statistical Inference in Financial and Insurance Mathematics with R written by Alexandre Brouste and published by Elsevier. This book was released on 2017-11-22 with total page 204 pages. Available in PDF, EPUB and Kindle. Book excerpt: Finance and insurance companies are facing a wide range of parametric statistical problems. Statistical experiments generated by a sample of independent and identically distributed random variables are frequent and well understood, especially those consisting of probability measures of an exponential type. However, the aforementioned applications also offer non-classical experiments implying observation samples of independent but not identically distributed random variables or even dependent random variables. Three examples of such experiments are treated in this book. First, the Generalized Linear Models are studied. They extend the standard regression model to non-Gaussian distributions. Statistical experiments with Markov chains are considered next. Finally, various statistical experiments generated by fractional Gaussian noise are also described. In this book, asymptotic properties of several sequences of estimators are detailed. The notion of asymptotical efficiency is discussed for the different statistical experiments considered in order to give the proper sense of estimation risk. Eighty examples and computations with R software are given throughout the text. - Examines a range of statistical inference methods in the context of finance and insurance applications - Presents the LAN (local asymptotic normality) property of likelihoods - Combines the proofs of LAN property for different statistical experiments that appears in financial and insurance mathematics - Provides the proper description of such statistical experiments and invites readers to seek optimal estimators (performed in R) for such statistical experiments


Statistical Inference in Financial and Insurance Mathematics with R Related Books

Statistical Inference in Financial and Insurance Mathematics with R
Language: en
Pages: 204
Authors: Alexandre Brouste
Categories: Mathematics
Type: BOOK - Published: 2017-11-22 - Publisher: Elsevier

DOWNLOAD EBOOK

Finance and insurance companies are facing a wide range of parametric statistical problems. Statistical experiments generated by a sample of independent and ide
Statistics and Data Analysis for Financial Engineering
Language: en
Pages: 736
Authors: David Ruppert
Categories: Business & Economics
Type: BOOK - Published: 2015-04-21 - Publisher: Springer

DOWNLOAD EBOOK

The new edition of this influential textbook, geared towards graduate or advanced undergraduate students, teaches the statistics necessary for financial enginee
Statistical Analysis of Financial Data in R
Language: en
Pages: 595
Authors: René Carmona
Categories: Business & Economics
Type: BOOK - Published: 2013-12-13 - Publisher: Springer Science & Business Media

DOWNLOAD EBOOK

Although there are many books on mathematical finance, few deal with the statistical aspects of modern data analysis as applied to financial problems. This text
Computational Actuarial Science with R
Language: en
Pages: 652
Authors: Arthur Charpentier
Categories: Business & Economics
Type: BOOK - Published: 2014-08-26 - Publisher: CRC Press

DOWNLOAD EBOOK

A Hands-On Approach to Understanding and Using Actuarial ModelsComputational Actuarial Science with R provides an introduction to the computational aspects of a
Computation and Modelling in Insurance and Finance
Language: en
Pages: 713
Authors: Erik Bølviken
Categories: Business & Economics
Type: BOOK - Published: 2014-04-10 - Publisher: Cambridge University Press

DOWNLOAD EBOOK

Focusing on what actuaries need in practice, this introductory account provides readers with essential tools for handling complex problems and explains how simu