Generalized error distribution parameter estimation

Function to fit the parameters of the generalized error distribution.

Usage

gedFit(x, ...)

Arguments

x: a numeric vector of quantiles.
...: parameters parsed to the optimization function nlm.

Value

gedFit returns a list with the following components:

par: The best set of parameters found.
objective: The value of objective corresponding to par.
convergence: An integer code, 0 indicates successful convergence.
message: A character string giving any additional information returned by the optimizer, or NULL. For details, see PORT documentation.
iterations: Number of iterations performed.
evaluations: Number of objective function and gradient function evaluations.

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.

Author

Diethelm Wuertz for the Rmetrics R-port

Examples

set.seed(1953)
r <- rged(n = 1000)

gedFit(r)
#> $par
#>        mean          sd          nu 
#> -0.01416477  1.00755265  1.85747923 
#> 
#> $objective
#> [1] 1425.889
#> 
#> $convergence
#> [1] 0
#> 
#> $iterations
#> [1] 19
#> 
#> $evaluations
#> function gradient 
#>       27       91 
#> 
#> $message
#> [1] "relative convergence (4)"
#>