gpdfit {loo} | R Documentation |
Estimate the parameters k and σ of the generalized Pareto distribution (assuming location parameter is 0), given a sample x. By default the Pareto fit uses a prior for k, which will stabilize estimates for very small sample sizes and low effective sample sizes in the case of MCMC samples. The weakly informative prior is a Gaussian prior centered at 0.5.
gpdfit(x, wip = TRUE, min_grid_pts = 30, sort_x = TRUE)
x |
A numeric vector. The sample from which to estimate the parameters. |
wip |
Logical indicating whether to adjust k based on a weakly
informative Gaussian prior centered on 0.5. Defaults to |
min_grid_pts |
The minimum number of grid points used in the fitting
algorithm. The actual number used is |
sort_x |
If |
Here the parameter k is the negative of k in Zhang & Stephens (2009).
A named list with components k
and sigma
.
Zhang, J., and Stephens, M. A. (2009). A new and efficient estimation method for the generalized Pareto distribution. Technometrics 51, 316-325.
psis
, pareto-k-diagnostic
,
loo-package