Rate the Article: Kernel Density Estimation for Claim Size Distributions Using Shifted Power Transformation, IJSR, Call for Papers, Online Journal
International Journal of Science and Research (IJSR)

International Journal of Science and Research (IJSR)
Call for Papers | Fully Refereed | Open Access | Double Blind Peer Reviewed

ISSN: 2319-7064

Downloads: 112 | Views: 416

Research Paper | Statistics | India | Volume 5 Issue 4, April 2016 | Rating: 6.6 / 10


Kernel Density Estimation for Claim Size Distributions Using Shifted Power Transformation

K. M. Sakthivel, C. S. Rajitha


Abstract: This paper presents density estimation of univariate claim severity distributions using kernel density estimation. We applied transformations to data prior to implement kernel density estimation so as to ensure the data is symmetry for the purpose of applying Gaussian methods. The paper presents non-parametric method of obtaining density for univariate claim severity distributions with goodness fits analysis for Danish insurance data on fire loss claims.


Keywords: Kernel density, bandwidth, Power transformation, Loss modeling, Cross validation


Edition: Volume 5 Issue 4, April 2016,


Pages: 2025 - 2028



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