mse: Calculate Mean Squared Error( MSE) by using different Kernels
In DELTD: Kernel Density Estimation using Lifetime Distributions

mse	R Documentation

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)

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"`.

Value

Mean Squared Error (MSE)

Author(s)

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.
## Not run: 
mse(kernel = gr, type ="Beta")

## End(Not run)

DELTD documentation built on Sept. 21, 2022, 9:10 a.m.