A new non parametric estimator for Pdf based on inverse gamma distribution |
| |
Authors: | A M Mousa A Fathi |
| |
Institution: | 1. Institute of Statistical Studies and Research, Cairo University, Giza, Egypt;2. Department of Mathematics, Faculty of Education, Ain Shams University, Cairo, Egypt |
| |
Abstract: | ABSTRACTThe non parametric approach is considered to estimate probability density function (Pdf) which is supported on(0, ∞). This approach is the inverse gamma kernel. We show that it has same properties as gamma, reciprocal inverse Gaussian, and inverse Gaussian kernels such that it is free of the boundary bias, non negative, and it achieves the optimal rate of convergence for the mean integrated squared error. Also some properties of the estimator were established such as bias and variance. Comparison of the bandwidth selection methods for inverse gamma kernel estimation of Pdf is done. |
| |
Keywords: | boundary bias inverse gamma kernel density estimation bandwidth |
|
|