000			02378nam 22002893 4500
001			88073
010			_a9780511755408 _dCompra
090			_a88073
100			_a20210914d2008 k||y0pory50 ba
101			_aeng
102			_aAU
200			_aGeneralized linear models for insurance data _bDocumento eletrónico _fPiet de Jong, Gillian Z. Heller
210			_aSydney _cCambridge University Press _d2008
215			_aX, 196 p. _cil.
330			_aGeneralized linear modeling is a methodology for modeling relationships between variables. It generalizes the classical normal linear model, by relaxing some of its restrictive assumptions, and provides methods for the analysis of non-normal data. The tools date back to the original article by Nelder and Wedderburn (1972) and have since become part of mainstream statistics, used in many diverse areas of application. This text presents the generalized linear model (GLM) methodology, with applications oriented to data that actuarial analysts are likely to encounter, and the analyses that they are likely required to perform. With the GLM, the variability in one variable is explained by the changes in one or more other variables. The variable being explained is called the “dependent” or “response” variable, while the variables that are doing the explaining are the “explanatory” variables. In some contexts these are called “risk factors” or “drivers of risk.” The model explains the connection between the response and the explanatory variables. Statistical modeling in general and generalized linear modeling in particular is the art or science of designing, fitting and interpreting a model. A statistical model helps in answering the following types of questions: Which explanatory variables are predictive of the response, and what is the appropriate scale for their inclusion in the model? Is the variability in the response well explained by the variability in the explanatory variables? […]
606			_aMatemática atuarial
606			_aModelos lineares (Matemática)
606			_aSeguros (Matemática)
680			_aHG8781
700			_aJong _bPiet de
701			_aHeller _bGillian Z. _4070 _961476
801			_gRPC
856			_uhttps://doi.org/10.1017/CBO9780511755408
942			_2lcc _cF _n0