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Showing 1 results for Rajabi
Mrs Leila Rajabi, Dr Behzad Mansouri,
Volume 27, Issue 2 (3-2023)
Abstract
Kernel density estimation is a standard method for estimating the probability density function, which in many cases works well. However, it has been found that it does not work well for negative, sloping, and wide-tail distributions, which are common features of the distribution of longevity, income, and so on. The purpose of this paper is to evaluate the performance of multiplicative bias correction (MBC) methods using asymmetric kernel estimators and compare this estimator with other boundary problem solving methods. In this paper, in addition to introducing MBC methods in combination with asymmetric kernel estimators, a simulation study shows that this estimator can, in some cases, provide a much better fit for density estimation than the standard kernel estimator. MBC methods using asymmetric kernel estimators were also used to estimate the lifetime density of transplanted corneas in 119 patients.
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