Statistical inference in financial and insurance with R
Brouste, Alexandre
Statistical inference in financial and insurance with R Alexandre Brouste ; Coordinated by Nikolaos Limnios and Yuliya Mishura - UK : Elsevier, c2018. - xv, 186 p. : ill. ; 24 cm. - Optimization in insurance and finance set .
This book examines a range of statistical inference methods in the context of finance and insurance applications, including asymptotical efficiency to give the proper notion of estimation risk, computations with the provided software R, and non-classical statistical experiments. As finance and insurance companies face a wide range of mathematical problems, and statistical experiments with independent and identically distributed samples are relatively common, this book covers topics of value to a wide group. Two examples are treated, including generalized linear models (GLM) extending to non-Gaussian samples (the standard regression method) and homogeneous Markov chains.
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
9781785480836
Finance--Mathematical models
Insurance--Mathematical models
BUSINESS & ECONOMICS / Finance
519.2 BR ST
Statistical inference in financial and insurance with R Alexandre Brouste ; Coordinated by Nikolaos Limnios and Yuliya Mishura - UK : Elsevier, c2018. - xv, 186 p. : ill. ; 24 cm. - Optimization in insurance and finance set .
This book examines a range of statistical inference methods in the context of finance and insurance applications, including asymptotical efficiency to give the proper notion of estimation risk, computations with the provided software R, and non-classical statistical experiments. As finance and insurance companies face a wide range of mathematical problems, and statistical experiments with independent and identically distributed samples are relatively common, this book covers topics of value to a wide group. Two examples are treated, including generalized linear models (GLM) extending to non-Gaussian samples (the standard regression method) and homogeneous Markov chains.
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
9781785480836
Finance--Mathematical models
Insurance--Mathematical models
BUSINESS & ECONOMICS / Finance
519.2 BR ST