×

On the \(r\mathcal{B}ell\) family of distributions with actuarial applications. (English) Zbl 1484.91373

Summary: In this paper, a new three-parameter discrete family of distributions, the \(r\mathcal{B}ell\) family, is introduced. The family is based on series expansion of the \(r\)-Bell polynomials. The proposed model generalises the classical Poisson and the recently proposed Bell and Bell-Touchard distributions. It exhibits interesting stochastic properties. Its probabilities can be computed by a recursive formula that allows us to calculate the probability function of the amount of aggregate claims in the collective risk model in terms of an integral equation. Univariate and bivariate regression models are presented. The former regression model is used to explain the number of out-of-use claims in an automobile insurance portfolio, by showing a good out-of-sample performance. The latter is used to describe the number of out-of-use and parking claims jointly. This family provides an alternative to other traditionally used distributions to describe count data such as the negative binomial and Poisson-inverse Gaussian models.

MSC:

91G05 Actuarial mathematics
62P05 Applications of statistics to actuarial sciences and financial mathematics
Full Text: DOI

References:

[1] Bell, E. T. (1934a). Exponential polynomials. Annals of Mathematical, 35(2), 258-277. · Zbl 0009.21202
[2] Bell, E. T. (1934b). Exponential numbers. The American Mathematical Monthly, 41(7), 411-419. · JFM 60.0116.01
[3] Bender, E. A., and Canfield, E. R. (1996). Log-concavity and related properties of the cycle index polynomials. Journal of Combinatorial Theory, Series A, 74(1), 57-70. · Zbl 0853.05013
[4] Bolancé, C. and Vernic, R. (2019). Multivariate count data generalized linear models: Three approaches based on the Sarmanov distribution. Insurance: Mathematics and Economics, 85(2019), 89-103. · Zbl 1415.62077
[5] Broder, A.Z. (1984). The r-Stirling numbers, Discrete Mathematics, 49, 241-259. · Zbl 0535.05006
[6] Boucher, J.P., Denuit, M. and Guillén, M. (2008). Models of insurance claim counts with time dependence based on generalization of Poisson and negative binomial distributions. Variance, 2(1):135-162.
[7] Calderín-Ojeda, E., Gómez-Déniz, E. and Barranco-Chamorro, I. (2019). Modelling zero-inflated count data with a special case of the generalised poisson distribution. Astin Bulletin, 49(3):689-707. · Zbl 1427.91220
[8] Castellares, F., Ferrari, S. L., and Lemonte, A. J. (2018). On the Bell distribution and its associated regression model for count data. Applied Mathematical Modelling, 56, 172-185. · Zbl 1480.60028
[9] Castellares, F., Lemonte, A. J., and Moreno-Arenas, G. (2019). On the two-parameter Bell-Touchard discrete distribution. Communications in Statistics-Theory and Methods, 1-19.
[10] Denuit, M., and Lamber, P. (2005). Constraints on concordance measures in bivariate discrete data. Journal of Multivariate Analysis, 93(1), 40-57. · Zbl 1095.62065
[11] Famoye, F. (2010). On the bivariate negative binomial regression model. Journal of Applied Statistics, 37(6), 969-981. · Zbl 1511.62176
[12] Jánossy, L., Rényi, A. and Aczél, J. (1950). On composed Poisson distributions, I, Acta Mathematica Academiae Scientiarum Hungaricae, 1(2-4):209-224. · Zbl 0041.24901
[13] Johnson, N.L, Kemp, A.W and Kotz, S. (2005). Univariate discrete distributions, Third Edition. Wiley Series in Probability and Statistics. Hoboken, NJ. · Zbl 1092.62010
[14] Kamp, U. (1998). On a class of premium principles including the Esscher principle. Scandinavian Actuarial Journal, 1, 75-80. · Zbl 1031.62505
[15] Kemp, C.D. (1967). On a contagious distribution suggested for accident data, Biometrics, 23(2):241-255.
[16] Keilson, J., and Gerber, H.(1971). Some result for discrete unimodality. Journal of American Statistical Association, 66 (334), 386-389. · Zbl 0236.60017
[17] Panjer, Klugman, S.A. and Willmot, G.E. (2008). Loss Models: From Data to Decisions, 3rd ed., Wiley, New York, 2008. · Zbl 1159.62070
[18] Lee, S.C.K (2021). Addressing imbalanced insurance data through zero-inflated Poisson regression with boosting. Astin Bulletin51(1): 27-55. · Zbl 1471.91466
[19] Li, C.S., Lu, J.C., Park, J., Kiim, K., Brinkley, P., and Peterson, J. (1999). Multivariate zero-inflated Poisson models and their applications. Technometrics, 41(1):29-38.
[20] Liu, F., and Pitt, D. (2017) Application of bivariate negative binomial regression model in analysing insurance count data, Annals of Actuarial Science, 11(2), 390-411.
[21] Touchard, J. (1933). PropriÉtÉs arihtmÉtiques de certains nombres rÉcurrents. Annales de la SociÉtÉ Scientifique de Bruxelles, 53, 21-31. · Zbl 0006.29102
[22] Mezö, I. (2011). The r-Bell Numbers, Journal of Integer Sequences, 14(1), 1-14. · Zbl 1205.05017
[23] Papageorgiou, H. and Piperigou, V.E. (1997). On bivariate ‘Short’ and related distributions, In: Advances in the Theory and Practice of Statistics-A Volume in Honor of Samuel Kotz (N.L. Johnson, and N. Balakrishnan, Eds.), 397-413, New York: John Wiley & Sons · Zbl 0887.62018
[24] Puig, P. and Valero, J. (2006). Count Data Distributions: Some Characterizations with applications. Journal of the American Statistical Association, 101 (473), 332-340. · Zbl 1118.62307
[25] Rolski, T., Schmidli, H., Schmidth, V., Teugels, J. (1999). Stochastic Process for Insurance and Finance. John Wiley and Sons, New York. · Zbl 0940.60005
[26] Vuong, Q. (1989). Likelihood ratio tests for model selection and non-nested hypotheses. Econometrica, 57, 2, 307-333. · Zbl 0701.62106
[27] Yan, H. R., Zhang, Q. L., and Xu, A. M. (2019). Some Inequalities for Generalized Bell-Touchard Polynomial. Journal of Mathematical Inequalities, 13(3), 645-653. · Zbl 1425.11048
This reference list is based on information provided by the publisher or from digital mathematics libraries. Its items are heuristically matched to zbMATH identifiers and may contain data conversion errors. In some cases that data have been complemented/enhanced by data from zbMATH Open. This attempts to reflect the references listed in the original paper as accurately as possible without claiming completeness or a perfect matching.