PL EN


Preferencje help
Widoczny [Schowaj] Abstrakt
Liczba wyników
2014 | 176
Tytuł artykułu

Taryfikacja w ubezpieczeniach majątkowych z wykorzystaniem modeli mieszanych

Warianty tytułu
Języki publikacji
PL
Abstrakty
Celem niniejszej pracy jest zatem zaproponowanie modeli statystycznych do taryfikacji uwzględniających obecną specyfikę masowych portfeli ubezpieczeniowych traktowanych jako zbiory obserwacji - próby statystyczne. Formalnie proponowane modele są regresyjnymi modelami mieszanymi klasy HGLM (ozn. Hierarchical Generalized Linear Model (HGLM)) oraz NLMM (ozn. Non-Linear Mixed Model (NLMM)). (fragment tekstu)
Rocznik
Strony
176
Opis fizyczny
Twórcy
  • Uniwersytet Ekonomiczny w Katowicach
Bibliografia
  • Antonio K., Beirlant J. (2007), Actuarial statistics with generalized linear mixed models, "Insurance: Mathematics and Economics", 40(1).
  • Antonio K., Beirlant J., Hoedemakers T., Verlaak R. (2006), Lognormal mixed models for reported claims reserves, "North American Actuarial Journal", 10(1).
  • Antonio K., Valdez E.A. (2012), Statistical concepts of a priori and a posteriori risk classification in insurance, "AStA Advances in Statistical Analysis", 96(2).
  • Beirlant J., Goegebeur Y., Segers J., Teugels J. (2006), Statistics of extremes: theory and applications, John Wiley & Sons.
  • Biecek P. (2011), Analiza danych z programem R: modele liniowe z efektami stalymi, losowymi i mieszanymi,, Wydawnictwo Naulcowe PWN.
  • Bjørnstad J.F. (1996), On the generalization of the likelihood function and the likelihood principle, "Journal of the American Statistical Association", 91(434).
  • Booth J.G., Hobert J.P. (1999), Maximizing generalized linear mixed model likelihoods with an automated Monte Carlo EM algorithm, "Journal of the Royal Statistical Society: Series B (Statistical Methodology)", 61(1).
  • Boucher J., Denuit M. (2006), Fixed versus random effects in Poisson regression models for claim counts: A case study with motor insurance, "Astin Bulletin", 36(1).
  • Boucher J.P., Denuit M., Guillen M. (2007), Risk Classification for Claim Counts: A Comparative Analysis of Various Zeroinflated Mixed Poisson and Hurdle Models, "North American Actuarial Journal", 11(4).
  • Boucher J.P., Denuit M., Guillen M. (2009), Number of Accidents or Number of Claims? An Approach with Zero-Inflated Poisson Models for Panel Data, "Journal of Risk and Insurance", 76(4).
  • Boucher J.P., Guillen M. (2009), A survey on models for panel count data with applications to insurance, "RACSAM-Revista de la Real Academia de Ciencias Exactas, Fisicas y Naturales. Serie A. Matematicas", 103(2).
  • Boucher J.P., Inoussa R. (2014), A posteriori ratemaking with panel data, "ASTIN Bulletin", DOI: http://dx.doi.org/10.1017/asb.2014.ll (About DOI), Published online: 23 April 2014.
  • Breslow N.E., Clayton D.G. (1993), Approximate inference in generalized linear mixed models, "Journal of the American Statistical Association", 88(421).
  • Van den Broek J. (1995), A score test for zero inflation in a Poisson distribution, "Biometrics".
  • Broström G., Holmberg H. (2011), Generalized linear models with clustered data: Fixed and random effects models, "Computational Statistics Data Analysis", 55(12).
  • Brown H., Prescott R. (2006), Applied mixed models in medicine, John Wiley &; Sons.
  • Bühlmann H., Gisler A. (2005), A course in credibility theory and its applications, Springer.
  • Cieślik B. (2004), System bonus-malus jako narzędzie konkurencji na rynku ubezpieczeń komunikacyjnych, w: Metody ilościowe w naukach ekonomicznych, "Oficyna Wydawnicza SGH, Warszawa".
  • Cizek P., Härdle W.K., Weron R. (2005), Statistical tools for finance and insurance, Springer.
  • Consul P., Famoye F. (1992), Generalized Poisson regression model, "Communications in Statistics-Theory and Methods", 21(1).
  • Consul P.C., Jain G.C. (1973), A generalization of the Poisson distribution, "Technometrics", 15(4).
  • Czado C., Erhardt V., Min A., Wagner S. (2007), Zero-inflated, generalized Poisson models with regression effects on the mean, dispersion and zero-inflation level applied to patent outsourcing rates, "Statistical Modelling", 7(2).
  • Davidian M., Giltinan D.M. (1995), Nonlinear models for repeated measurement data, tom 62, CRC Press.
  • De Jong P., Heller G.Z. (2008), Generalized linear models for insurance data, Cambridge University Press.
  • Dean C., Lawless J., Willmot G. (1989), A mixed poisson-inverse-gaussian regression model, "Canadian Journal of Statistics", 17(2).
  • Demidenko E. (2005), Mixed models: theory and applications, tom 518, John Wiley & Sons.
  • Denuit M., Maréchal X., Pitrebois S., Walhin J.F. (2007), Actuarial modelling of claim counts: Risk classification, credibility and bonus-malus systems, Wiley, com.
  • Desyllas P., Sako M. (2013), Profiting from business m,odel innovation: Evidence from Pay-As-You-Drive auto insurance, "Research Policy", 42(1).
  • Dimakos X.K., Di Rattalma A.F. (2002), Bayesian premium rating with latent structure, "Scandinavian Actuarial Journal", 2002(3).
  • Dionne G., Vanasse C. (1989), A generalization of automobile insurance rating models: the negative binomial distribution with a regression component, "Astin Bulletin", 19(2).
  • Dionne G., Vanasse C. (1992), Automobile insurance ratemaking in the presence of asymmetrical information, "Journal of Applied Econometrics", 7(2).
  • Dunn P.K., Smyth G.K. (2005), Series evaluation of Tweedie exponential dispersion model densities, "Statistics and Computing", 15(4).
  • Dunn P.K., Smyth G.K. (2008), Evaluation of Tweedie exponential dispersion model densities by Fourier inversion, "Statistics and Computing", 18(1).
  • Famoye F., Singh K.P. (2006), Zero-inflated generalized Poisson regression model with an application to domestic violence data, "Journal of Data Science", 4(1).
  • Famoye F., Wulu J., Singh K.P. (2004), On the generalized Poisson regression model with an application to accident data, "Journal of Data Science", 2(2004).
  • Frątczak E. (2013), Zaawansowane modele analiz statystycznych, Oficyna Wydawnicza SGH.
  • Frees E.W. (2009), Regression modeling with actuarial and financial applications, Cambridge University Press.
  • Frees E.W., Derrig R.A., Meyers G. (2014), Predictive modeling applications in actuarial science, Cambridge University Press.
  • Gnot S. (1991), Estymacja komponentów wariancyjnych w modelach liniowych, WNT, Warszawa.
  • Gray R.J., Pitts S.M. (2012), Risk Modelling in General Insurance: From Principles to Practice, Cambridge University Press.
  • Greenwood M., Yule G.U. (1920), An inquiry into the nature of frequency distributions representative of multiple happenings with particular reference to the occurrence of multiple attacks of disease or of repeated accidents, "Journal of the Royal Statistical Society".
  • Gumpertz M.L., Pantula S.G. (1992), Nonlinear regression with variance components, "Journal of the American Statistical Association".
  • Haberman S., Renshaw A.E. (1996), Generalized linear models and actuarial science, "The Statistician".
  • Joe H., Zhu R. (2005), Generalized Poisson distribution: the property of mixture of Poisson and comparison with negative binomial distribution, "Biometrical Journal".
  • Jørgensen B. (1986), Some properties of exponential dispersion models, "Scandinavian Journal of Statistics".
  • Jørgensen B. (1987), Exponential dispersion models, "Journal of the Royal Statistical Society. Series B (Methodological)".
  • Jørgensen B., Paes De Souza M.C. (1994), Fitting Tweedie's compound Poisson model to insurance claims data, "Scandinavian Actuarial Journal", 1994(1).
  • Karlis D. (2005), EM algorithm for mixed Poisson and other discrete distributions, "Astin bulletin".
  • Karlis D., Xekalaki E. (2005), Mixed poisson distributions, "International Statistical Review", 73(1).
  • Kowalczyk P., Poprawska E., Ronka-Chmielowiec W. (2006), Metody aktuarialne, Wydawnictwo Naukowe PWN, Warszawa.
  • Laird N.M., Ware J.H. (1982), Random-effects models for longitudinal data, "Biometrics".
  • Lambert D. (1992), Zero-inflated Poisson regression, with an application to defects in manufacturing, "Technometrics", 34(1).
  • Lawless J.F. (1987), Negative binomial and mixed Poisson regression, "Canadian Journal of Statistics", 15(3).
  • Lee Y., Nelder J.A. (1996), Hierarchical generalized linear models, "Journal of the Royal Statistical Society. Series B (Methodological)".
  • Lee Y., Nelder J.A. (2001), Hierarchical generalised linear models: a synthesis of generalised linear models, random-effect models and structured dispersions, "Biometrika", 88(4).
  • Lee Y., Nelder J.A., Pawitan Y. (2006), Generalized linear models with random effects: unified analysis via H-likelihood, CRC Press.
  • Lemaire J. (1995), Bonus-malus systems in automobile insurance, tom 19, Springer.
  • Lindsey J.K. (1997), Applying generalized linear models, Springer.
  • Littell R.C. (2006), SAS for mixed models, SAS institute.
  • Marzec J. (2008), Bayesowskie modele zmiennych jakościowych i ograniczonych w badaniach niespłacalności kredytów, "Zeszyty Naukowe/Uniwersytet Ekonomiczny w Krakowie. Seria Specjalna, Monografie", (188).
  • McCullagh P., Nelder J. (1989), Generalized linear models. Second Edition, "Monographs on statistics and applied probability.".
  • McCulloch C.E. (2006), Generalized linear mixed models, Wiley Online Library.
  • Mildenhall S.J. (1999), A systematic relationship between minimum bias and generalized linear models, w: Proceedings of the Casualty Actuarial Society, tom 86.
  • Molenberghs G., Verbeke G. (2005), Models for discrete longitudinal data, Springer.
  • Murphy K.P., Brockman M.J., Lee P.K. (2000), Using generalized linear models to build dynamic pricing systems, w: Casualty Actuarial Society Forum., Winter.
  • Nelder J., Verrall R. (1997), Credibility theory and generalized linear models, "Astin Bulletin".
  • Nelder J., Wedderburn W. (1972), Generalized Linear Models, "Journal of the Royal Statistical Society. Series A (General)", 135(3).
  • Nelder J.A., Mead R. (1965), A simplex method for function minimization, "The Computer Journal", 7(4).
  • Ohlsson E., Johansson B. (2010), Non-life insurance pricing with generalized linear models, Springer.
  • Ostasiewicz W., Dębicka J. (2004), Składki i ryzyko ubezpieczeniowe: modelowanie stochastyczne, Wydawnictwo Akademii Ekonomicznej, Wrocław.
  • Otto W. (2013), Ubezpieczenia majątkowe-Część I-Teoria ryzyka, wydanie drugie.
  • Panjer H.H. (1981), Recursive evaluation of a family of compound distributions, "Astin Bulletin", 12(1).
  • Pawitan Y. (2001), In all likelihood: statistical modelling and inference using likelihood, Oxford University Press.
  • Pinheiro J.C., Bates D.M. (1995), Approximations to the log-likelihood function in the nonlinear mixed-effects model, "Journal of Computational and Graphical Statistics", 4(1).
  • Pinheiro J.C., Bates D.M. (2000), Linear mixed-effects models: basic concepts and examples, Springer.
  • Pinquet J. (2000), Experience rating through heterogeneous models, w: Handbook of Insurance, Springer.
  • Pitkanen P. (1975), Tariff theory, "International Journal for Actuarial Studies in Non-life Insurance and Risk Theory".
  • Podgórska M. (2008), System bonus-malus sprawiedliwy w sensie przejść między klasami, "Prace Naukowe Uniwersytetu Ekonomicznego we Wrocławiu", (1 (1201)).
  • R Core Team (2013), R: A Language and Environment for Statistical Computing, R Foundation for Statistical Computing, Vienna, Austria.
  • Ridout M., Demétrio C.G., Hinde J. (1998), Models for count data with many zeros, w: Proceedings of the XlXth International Biometric Conference, tom 19.
  • Rigby R., Stasinopoulos D. (2005), Generalized additive models for location, scale and shape, "Journal of the Royal Statistical Society: Series C (Applied Statistics)", 54(3).
  • Ronka-Chmielowiec W. (1997), Ryzyko w ubezpieczeniach-metody oceny, Wydawnictwo Akademii Ekonomicznej, Wrocław.
  • Sarma K.S. (2013), Predictive modeling with SAS Enterprise Miner: practical solutions for business applications, SAS Institute.
  • Sichel H.S. (1975), On a distribution law for word frequencies, "Journal of the American Statistical Association", 70(351a).
  • Smyth G.K. (1989), Generalized linear models with varying dispersion, "Journal of the Royal Statistical Society. Series B (Methodological)".
  • Smyth G.K., Jørgensen B. (2002), Fitting Tweedie's compound Poisson model to insurance claims data: dispersion modelling, "Astin Bulletin", 32(1).
  • Sobiecki D. (2013), Dwustopniowe modelowanie składki za ubezpieczenie komunikacyjne OC, "Prace Naukowe Uniwersytetu Ekonomicznego we Wrocławiu", (312).
  • Straub E. (1988), Non-Life Insurance Mathematics, Springer.
  • Szymańska A. (2008), Wybrane miary efektywności systemów bonus-malus ubezpieczeń komunikacyjnych OC, "Prace Naukowe Akademii Ekonomicznej we Wrocławiu", (1197).
  • Tweedie M. (1984), An index which distinguishes between some important exponential families, w: Statistics: Applications and New Directions: Proc. Indian Statistical Institute Golden Jubilee International Conference.
  • Venables W.N., Ripley B.D. (2002), Modern applied statistics with S, Springer.
  • Verbeke G., Lesaffre E. (1996), A linear mixed-effects model with heterogeneity in the random-effects population, "Journal of the American Statistical Association", 91(433).
  • Vonesh E.F., Chinchilli V.M. (1997), Linear and nonlinear models for the analysis of repeated measurements, tom 1, CRC press.
  • Wanat S. (2012), Modele zależności w agregacji ryzyka ubezpieczyciela, "Zeszyty Naukowe/Uniwersytet Ekonomiczny w Krakowie. Seria Specjalna, Monografie", (211).
  • Werner G., Modlin C. (2010), Basic ratemaking, w: Casualty Actuarial Society.
  • West B.T., Welch K.B., Gałecki A.T. (2006), Linear mixed models: a practical guide using statistical software, GRC Press.
  • Winkelmann R. (2003), Econometric analysis of count data, Springer.
  • Wolfinger R. (1993), Laplace's approximation for nonlinear mixed models, "Biometrika", 80(4).
  • Wolny-Dominiak A. (2012), Modeling of claim counts using data mining procedures in R CRAN, w: Proceedings of 30th International Conference Mathematical Methods in Economics.
  • Wolny-Dominiak A. (2013), Zero-inflated claim, count modeling and testing-a case study, "Ekonometria", (1 (39)).
  • Yang Z., Hardin J.W., Addy C.L. (2009), Testing overdispersion in the zero-inflated Poisson model, "Journal of Statistical Planning and Inference", 139(9).
  • Yip K.C., Yau R.K. (2005), On modeling claim frequency data in general insurance with extra zeros, "Insurance: Mathematics and Economics", 36(2).
  • Żądło T. (2014), On the Prediction of the Subpopulation Total Based on Spatially Correlated Longitudinal Data, "Mathematical Population Studies", 21(1).
  • Zhang Y. (2013), Likelihood-based and bayesian methods for tweedie compound poisson linear mixed models, "Statistics and Computing", 23(6).
Typ dokumentu
Bibliografia
Identyfikatory
Identyfikator YADDA
bwmeta1.element.ekon-element-000171388769

Zgłoszenie zostało wysłane

Zgłoszenie zostało wysłane

Musisz być zalogowany aby pisać komentarze.
JavaScript jest wyłączony w Twojej przeglądarce internetowej. Włącz go, a następnie odśwież stronę, aby móc w pełni z niej korzystać.