Generalized Linear Models in Vehicle Insurance

J 2014

Generalized Linear Models in Vehicle Insurance

KAFKOVÁ, Silvie a Lenka KŘIVÁNKOVÁ

Základní údaje

Originální název

Generalized Linear Models in Vehicle Insurance

Autoři

KAFKOVÁ, Silvie (203 Česká republika, garant, domácí) a Lenka KŘIVÁNKOVÁ (203 Česká republika, domácí)

Vydání

Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis, Mendelova univerzita v Brně, 2014, 1211-8516

Další údaje

Jazyk

angličtina

Typ výsledku

Článek v odborném periodiku

Obor

50600 5.6 Political science

Stát vydavatele

Česká republika

Utajení

není předmětem státního či obchodního tajemství

Odkazy

URL

Kód RIV

RIV/00216224:14560/14:00075556

Organizační jednotka

Ekonomicko-správní fakulta

DOI

http://dx.doi.org/10.11118/actaun201462020383

EID Scopus

2-s2.0-84901770103

Klíčová slova anglicky

vehicle insurance; generalized linear model; poisson distribution; link function; analysis of deviance; Akaike information criterion

Příznaky

Mezinárodní význam, Recenzováno

Změněno: 31. 3. 2015 13:36, Mgr. et Mgr. Nikol Zachovalová Barochová

Anotace

V originále

Actuaries in insurance companies try to find the best model for an estimation of insurance premium. It depends on many risk factors, e.g. the car characteristics and the profile of the driver. In this paper, an analysis of the portfolio of vehicle insurance data using a generalized linear model (GLM) is performed. The main advantage of the approach presented in this article is that the GLMs are not limited by inflexible preconditions. Our aim is to predict the relation of annual claim frequency on given risk factors. Based on a large real-world sample of data from 57 410 vehicles, the present study proposed a classification analysis approach that addresses the selection of predictor variables. The models with different predictor variables are compared by analysis of deviance and Akaike information criterion (AIC). Based on this comparison, the model for the best estimate of annual claim frequency is chosen. All statistical calculations are computed in R environment, which contains stats package with the function for the estimation of parameters of GLM and the function for analysis of deviation.

Citovat

KAFKOVÁ, Silvie a Lenka KŘIVÁNKOVÁ. Generalized Linear Models in Vehicle Insurance. Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis. Mendelova univerzita v Brně, 2014, roč. 62, č. 2, s. 383-388. ISSN 1211-8516. Dostupné z: https://dx.doi.org/10.11118/actaun201462020383.

@article{1183811,
   author = {Kafková, Silvie and Křivánková, Lenka},
   article_number = {2},
   doi = {http://dx.doi.org/10.11118/actaun201462020383},
   keywords = {vehicle insurance; generalized linear model; poisson distribution; link function; analysis of deviance; Akaike information criterion},
   language = {eng},
   issn = {1211-8516},
   journal = {Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis},
   title = {Generalized Linear Models in Vehicle Insurance},
   url = {http://acta.mendelu.cz/62/2/0383/},
   volume = {62},
   year = {2014}
}

TY  - JOUR
ID  - 1183811
AU  - Kafková, Silvie - Křivánková, Lenka
PY  - 2014
TI  - Generalized Linear Models in Vehicle Insurance
JF  - Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis
VL  - 62
IS  - 2
SP  - 383-388
EP  - 383-388
PB  - Mendelova univerzita v Brně
SN  - 12118516
KW  - vehicle insurance
KW  - generalized linear model
KW  - poisson distribution
KW  - link function
KW  - analysis of deviance
KW  - Akaike information criterion
UR  - http://acta.mendelu.cz/62/2/0383/
L2  - http://acta.mendelu.cz/62/2/0383/
N2  - Actuaries in insurance companies try to find the best model for an estimation of insurance premium. It depends on many risk factors, e.g. the car characteristics and the profile of the driver. In this paper, an analysis of the portfolio of vehicle insurance data using a generalized linear model (GLM) is performed. The main advantage of the approach presented in this article is that the GLMs are not limited by inflexible preconditions. Our aim is to predict the relation of annual claim frequency on given risk factors. Based on a large real-world sample of data from 57 410 vehicles, the present study proposed a classification analysis approach that addresses the selection of predictor variables. The models with different predictor variables are compared by analysis of deviance and Akaike information criterion (AIC). Based on this comparison, the model for the best estimate of annual claim frequency is chosen. All statistical calculations are computed in R environment, which contains stats package with the function for the estimation of parameters of GLM and the function for analysis of deviation.
ER  -

KAFKOVÁ, Silvie a Lenka KŘIVÁNKOVÁ. Generalized Linear Models in Vehicle Insurance. \textit{Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis}. Mendelova univerzita v Brně, 2014, roč.~62, č.~2, s.~383-388. ISSN~1211-8516. Dostupné z: https://dx.doi.org/10.11118/actaun201462020383.

Přehled o publikaci