# dist-ged: Standardized generalized error distribution In fGarch: Rmetrics - Autoregressive Conditional Heteroskedastic Modelling

 ged R Documentation

## Standardized generalized error distribution

### Description

Functions to compute density, distribution function, quantile function and to generate random variates for the standardized generalized error distribution.

### Usage

```dged(x, mean = 0, sd = 1, nu = 2, log = FALSE)
pged(q, mean = 0, sd = 1, nu = 2)
qged(p, mean = 0, sd = 1, nu = 2)
rged(n, mean = 0, sd = 1, nu = 2)
```

### Arguments

 `x, q` a numeric vector of quantiles. `p` a numeric vector of probabilities. `n` number of observations to simulate. `mean` location parameter. `sd` scale parameter. `nu` shape parameter. `log` logical; if `TRUE`, densities are given as log densities.

### Details

The standardized GED is defined so that for a given `sd` it has the same variance, `sd^2`, for all values of the shape parameter.

`dstd` computes the density, `pstd` the distribution function, `qstd` the quantile function, and `rstd` generates random deviates from the standardized-t distribution with the specified parameters.

numeric vector

### Author(s)

Diethelm Wuertz for the Rmetrics R-port

### References

Nelson D.B. (1991); Conditional Heteroscedasticity in Asset Returns: A New Approach, Econometrica, 59, 347–370.

Fernandez C., Steel M.F.J. (2000); On Bayesian Modelling of Fat Tails and Skewness, Preprint, 31 pages.

`gedFit`, `absMoments`, `sged` (skew GED),

`gedSlider` for visualization

### Examples

```## sged -
par(mfrow = c(2, 2))
set.seed(1953)
r = rsged(n = 1000)
plot(r, type = "l", main = "sged", col = "steelblue")

# Plot empirical density and compare with true density:
hist(r, n = 25, probability = TRUE, border = "white", col = "steelblue")
box()
x = seq(min(r), max(r), length = 201)
lines(x, dsged(x), lwd = 2)

# Plot df and compare with true df:
plot(sort(r), (1:1000/1000), main = "Probability", col = "steelblue",
ylab = "Probability")
lines(x, psged(x), lwd = 2)

# Compute quantiles:
round(qsged(psged(q = seq(-1, 5, by = 1))), digits = 6)

```

fGarch documentation built on Nov. 10, 2022, 5:48 p.m.