this paper, gamma kernel estimators of the density and the hazard rate function are proposed. The estimators use adaptive …

paper we propose the gamma kernel estimator as density estimator for positive data from a stationary ?-mixing process. We … generate data from an autoregressive conditional duration model and a stochastic volatility model, we find that the gamma … kernel outperforms the local linear density estimator. An application to data from financial transaction durations, realized …

paper we propose the gamma kernel estimator as density estimator for positive data from a stationary -mixing process. We … generate data from an autoregressive conditional duration model and a stochastic volatility model, we find that the gamma … kernel outperforms the local linear density estimator. An application to data from financial transaction durations, realized …

this paper, gamma kernel estimators of the density and the hazard rate function are proposed. The estimators use adaptive …

for actuarial applications. In this paper, we propose a new class of gamma kernel density estimators (GKDEs) based on the … advantages over the existing gamma kernel class by  Chen (2000) in that it is a valid density for any finite sample and has … flexibility, but with a straightforward implementation and optimization. As numerical examples, we fit the gamma kernel density …

general and positive recurrent processes and illustrate the advantages of the Gamma kernel for bias correction and efficiency …

functions used as kernels. We show that they share the same properties as those of gamma kernel estimators : they are free of …