The Relative Improvement of Bias Reduction in Density Estimator Using Geometric Extrapolated Kernel

Q: How can I download an article?

To download an article from SID, first log in to the site, search for the article title, and click on the 'Download Article' option.

Q: How can I download an ISI article?

To download an ISI article on SID, enter the keyword or article title in the search bar, view the relevant results, click on the desired article, and select the 'Download Article' option.

Q: How can I access the SID database?

To access the SID database, visit SID.ir, create an account, and log in to access scientific resources.

Q: Is downloading articles from SID free?

Some articles on SID are available for free, while others require payment. Details are specified on the article's page.

SALEHI REZA; SHADROKH ALI; YARMOHAMMADI MASOUD

مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

Journal Paper

Paper Information

Journal: MATHEMATICAL RESEARCHES Year:2019 | Volume:4 | Issue:2 Page(s): 211-228

Download Full-Text

Persian Verion

View:

468

Download:

170

Cites:

Information Journal Paper

Title

The Relative Improvement of Bias Reduction in Density Estimator Using Geometric Extrapolated Kernel

Author(s)

SALEHI REZA | SHADROKH ALI | YARMOHAMMADI MASOUD | Issue Writer Certificate

Keywords

Density estimationQ1

Smoothness parameterQ1

Geometric extrapolationQ1

Symmetric kernelQ1

BiasQ1

Abstract

The probability density function is a basic concept in statistics, which can be used to study all behaviors of a random variable; several nonparametric methods have been used to estimate the probability density function. One of a nonparametric procedure used to estimate densities is the kernel method. In this paper, to reduce Bias of kernel Density estimation, methods such as usual kernel (UK), geometric extrapolated usual kernel (GEUK), a Bias reduction kernel (BRK) and a geometric extrapolated Bias reduction kernel (GEBRK) are introduced. Theoretical properties, including the selection of Smoothness parameter and the accuracy of resultant estimators are studied. Accordingly, the mean integrated squared error of GEBRK method achieves a faster convergence rate when kernels are symmetric. ....

Cites

No record.

References

No record.

Cite

APA: Copy

SALEHI, REZA, SHADROKH, ALI, & YARMOHAMMADI, MASOUD. (2019). The Relative Improvement of Bias Reduction in Density Estimator Using Geometric Extrapolated Kernel. MATHEMATICAL RESEARCHES, 4(2 ), 211-228. SID. https://sid.ir/paper/260783/en

Vancouver: Copy

SALEHI REZA, SHADROKH ALI, YARMOHAMMADI MASOUD. The Relative Improvement of Bias Reduction in Density Estimator Using Geometric Extrapolated Kernel. MATHEMATICAL RESEARCHES[Internet]. 2019;4(2 ):211-228. Available from: https://sid.ir/paper/260783/en

IEEE: Copy

REZA SALEHI, ALI SHADROKH, and MASOUD YARMOHAMMADI, “The Relative Improvement of Bias Reduction in Density Estimator Using Geometric Extrapolated Kernel,” MATHEMATICAL RESEARCHES, vol. 4, no. 2 , pp. 211–228, 2019, [Online]. Available: https://sid.ir/paper/260783/en

Related Journal Papers