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:: Volume 27, Issue 2 (3-2023) ::
Andishe 2023, 27(2): 81-94 Back to browse issues page
Investigation of multiplicative bias correction method using asymmetric kernels
Leila Rajabi * , Behzad Mansouri
Abstract:   (516 Views)
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.

 
Keywords: Boundary problem, Asymmetric kernel, Multiplicative bias correction, lifetime density.
Full-Text [PDF 770 kb]   (286 Downloads)    
Type of Study: Applicable | Subject: Special
Received: 2023/02/12 | Accepted: 2023/05/19 | Published: 2023/05/19
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Rajabi L, Mansouri B. Investigation of multiplicative bias correction method using asymmetric kernels. Andishe 2023; 27 (2) :81-94
URL: http://andisheyeamari.irstat.ir/article-1-909-en.html


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Volume 27, Issue 2 (3-2023) Back to browse issues page
مجله اندیشه آماری Andishe _ye Amari
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