Zobrazeno 1 - 10
of 100
pro vyhledávání: '"Brazauskas, Vytaras"'
In this paper, the problem of robust estimation and validation of location-scale families is revisited. The proposed methods exploit the joint asymptotic normality of sample quantiles (of i.i.d random variables) to construct the ordinary and generali
Externí odkaz:
http://arxiv.org/abs/2402.07837
"The rich are getting richer" implies that the population income distributions are getting more right skewed and heavily tailed. For such distributions, the mean is not the best measure of the center, but the classical indices of income inequality, i
Externí odkaz:
http://arxiv.org/abs/2308.03708
To accommodate numerous practical scenarios, in this paper we extend statistical inference for smoothed quantile estimators from finite domains to infinite domains. We accomplish the task with the help of a newly designed truncation methodology for d
Externí odkaz:
http://arxiv.org/abs/2304.02723
When constructing parametric models to predict the cost of future claims, several important details have to be taken into account: (i) models should be designed to accommodate deductibles, policy limits, and coinsurance factors, (ii) parameters shoul
Externí odkaz:
http://arxiv.org/abs/2204.02477
In this paper, we consider robust estimation of claim severity models in insurance, when data are affected by truncation (due to deductibles), censoring (due to policy limits), and scaling (due to coinsurance). In particular, robust estimators based
Externí odkaz:
http://arxiv.org/abs/2202.13000
Publikováno v:
Quality & Quantity; Oct2024, Vol. 58 Issue 5, p4859-4896, 38p
Publikováno v:
North American Actuarial Journal; 2024, Vol. 28 Issue 3, p678-694, 17p
Publikováno v:
North American Actuarial Journal; 2024, Vol. 28 Issue 1, p236-260, 25p
Publikováno v:
In Insurance Mathematics and Economics May 2016 68:84-91
Autor:
Upretee, Sahadeb, Brazauskas, Vytaras
Publikováno v:
North American Actuarial Journal; 2023, Vol. 27 Issue 4, p689-709, 21p