# plot.Weibull: Density Plot by Weibull kernel In DEEVD: Density Estimation by Extreme Value Distributions

## Description

Plot density by using Weibull Kernel.

## Usage

 ```1 2``` ```## S3 method for class 'Weibull' plot(x, ...) ```

## Arguments

 `x` an object of class "Weibull" `...` Not presently used in this implementation

nothing

## References

Salha, R. B., El Shekh Ahmed, H. I., & Alhoubi, I. M. 2014. Hazard Rate Function Estimation Using Weibull Kernel. Open Journal of Statistics 4 (08), 650-661.

For Gumbel kernel see `plot.Gumbel`. To calculate Weibull estimated values see `Weibull` and for MSE use `mse`.
 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18``` ```y <- rlnorm(100, meanlog = 0, sdlog = 1) h <- 1.5 xx <- seq(min(y) + 0.05, max(y), length = 200) den <- Weibull(x = xx, y = y, k = 200, h = h) plot(den, type = "l") ##other details can also be added y <- rlnorm(100, meanlog = 0, sdlog = 1) grid <- seq(min(y) + 0.05, max(y), length = 200) h <- 0.79 * IQR(y) * length(y) ^ (-1/5) gr <- Weibull(x = grid, y = y, k = 200, h = h) plot(gr, type = "s", ylab = "Density Function", lty = 1, xlab = "Time") ## To add true density along with estimated d1 <- density(y, bw = h) lines(d1, type = "p", col = "green") legend("topright", c("Real Density", "Density by Weibull Kernel"), col=c("green", "black"), lty=c(1,2)) ```