The Linear Combination of Kernels in the Estimation Of Cumulative Distribution Functions
The kernel distribution function estimator method is the most popular nonparametric method to estimate the cumulative distribution function F(x). In this investigation, we propose a new estimator for F(x) based on a linear combination of kernels. The mean integrated squared error, asymptotic mean integrated squared error and the asymptotically optimal bandwidth for the new estimator are derived. Also, based on the plug-in technique in density estimation, we propose a data based method to select the bandwidth for the new estimator. In addition, we evaluate the new estimator using simulations and real life data.
Mugdadi, Abdel-Razzaq and Sani, Rugayyah
The Linear Combination of Kernels in the Estimation Of Cumulative Distribution Functions,
Applications and Applied Mathematics: An International Journal (AAM), Vol. 15,
2, Article 9.
Available at: https://digitalcommons.pvamu.edu/aam/vol15/iss2/9