DELTD (version 2.6.8)

mse: Calculate Mean Squared Error( MSE) by using different Kernels

Description

This function calculates the mean squared error (MSE) by using user specified kernel. But distribution of vector should be Exponential, Gamma or Weibull. Any other choice of distribution will result NaN.

Usage

mse(kernel, type)

Value

Mean Squared Error (MSE)

Arguments

kernel

type of kernel which is to be used

type

mention distribution of vector.If exponential distribution then use "Exp". If use gamma distribution then use "Gamma".If Weibull distribution then use "Weibull".

Author

Javaria Ahmad Khan, Atif Akbar.

References

• Jin, X.; Kawczak, J. 2003. Birnbaum-Saunders & Lognormal kernel estimators for modeling durations in high frequency financial data. Annals of Economics and Finance 4, 103-124.

• Salha, R. B.; Ahmed, E. S.; Alhoubi, I. M. 2014. Hazard rate function estimation using Erlang Kernel. Pure Mathematical Sciences 3 (4), 141-152.

• Chen, S. X. 2000. Probability density function estimation using Gamma kernels. Annals of the Institute of Statistical Mathematics 52 (3), 471-480.

• Chen, S. X. 2000. Beta kernel smothers for regression curves. Statistica Sinica 10, 73-91.

Examples

y <- rexp(100, 1)
xx <- seq(min(y) + 0.05, max(y), length = 500)
h <- 2
gr <- Gamma(x = xx, y = y, k = 200, h = h)
mse(kernel = gr, type = "Exp")
## if distribution is other than mentioned \code{type} is used then NaN will be produced.
if (FALSE) {
mse(kernel = gr, type ="Beta")
}