1 |
Bagnato L and Punzo A (2013). Finite mixtures of unimodal beta and gamma densities and the k-bumps algorithm, Computational Statistics, 28, 1571-1597.
DOI
|
2 |
Bakar SA, Hamzah NA, Maghsoudi M, and Nadarajah S (2015). Modeling loss data using composite models, Insurance: Mathematics and Economics, 61, 146-154.
DOI
|
3 |
Bernardi M, Maruotti A, and Petrella L (2012). Skew mixture models for loss distributions: a Bayesian approach, Insurance: Mathematics and Economics, 51, 617-623.
DOI
|
4 |
Bhati D and Ravi S (2018). On generalized log-Moyal distribution: A new heavy tailed size distribution, Insurance: Mathematics and Economics, 79, 247-259.
DOI
|
5 |
Cooray K and Ananda MM (2005). Modeling actuarial data with a composite lognormal-Pareto model, Scandinavian Actuarial Journal, 2005, 321-334.
DOI
|
6 |
Eling M (2012). Fitting insurance claims to skewed distributions: Are the skew-normal and skewstudent good models?, Insurance: Mathematics and Economics, 51, 239-248.
DOI
|
7 |
Garcia VJ, Gomez-Deniz E, and Vazquez-Polo FJ (2014). On modelling insurance data by using a generalized lognormal distribution, Revista de Metodos Cuantitativos para la Economia y la Empresa, 18, 146-162.
|
8 |
Glanzel W (1987). A characterization theorem based on truncated moments and its application to some distribution families. In Mathematical Statistics and Probability Theory (pp. 75-84), Springer, Dordrecht.
|
9 |
Glanzel W (1990). Some consequences of a characterization theorem based on truncated moments, Statistics, 21, 613-618.
DOI
|
10 |
Ibragimov R and Prokhorov A (2017). Heavy tails and copulas: topics in dependence modelling in economics and finance.
|
11 |
Kazemi R and Noorizadeh M (2015). A comparison between skew-logistic and skew-normal distributions, MATEMATIKA: Malaysian Journal of Industrial and Applied Mathematics, 31, 15-24.
|
12 |
Klugman SA, Panjer HH, and Willmot GE (2012). Loss Models: From Data to Decisions (4th ed), John Wiley and Sons, Hoboken, NJ.
|
13 |
Landsman Z, Makov U, and Shushi T (2016). Tail conditional moments for elliptical and log-elliptical distributions, Insurance: Mathematics and Economics, 71, 179-188.
DOI
|
14 |
Lane MN (2000). Pricing risk transfer transactions 1, ASTIN Bulletin: The Journal of the IAA, 30, 259-293.
DOI
|
15 |
Mahdavi A and Kundu D (2017). A new method for generating distributions with an application to exponential distribution, Communications in Statistics-Theory and Methods, 46, 6543-6557.
DOI
|
16 |
Punzo A, Bagnato L, and Maruotti A (2018). Compound unimodal distributions for insurance losses, Insurance: Mathematics and Economics, 81, 95-107.
DOI
|
17 |
Reynkens T, Verbelen R, Beirlant J, and Antonio K (2017). Modelling censored losses using splicing: A global fit strategy with mixed Erlang and extreme value distributions, Insurance: Mathematics and Economics, 77, 65-77.
DOI
|
18 |
Adcock C, Eling M, and Loperfido N (2015). Skewed distributions in finance and actuarial science: a review, The European Journal of Finance, 21, 1253-1281.
DOI
|
19 |
Ahmad Z, Hamedani GG, and Butt NS (2019a). Recent developments in distribution theory: a brief survey and some new generalized classes of distributions, Pakistan Journal of Statistics and Operation Research, 15, 87-110.
|
20 |
Ahmad Z, Ilyas M, and Hamedani GG (2019b). The extended alpha power transformed family of distributions: properties and applications, Journal of Data Science, 17, 726-741.
|
21 |
Artzner P (1999). Application of coherent risk measures to capital requirements in insurance, North American Actuarial Journal, 3, 11-25.
DOI
|