rl.pred: Return Level Plots for GEV Predictive Distributions
In evdbayes: Bayesian Analysis in Extreme Value Theory

rl.pred

R Documentation

Return Level Plots for GEV Predictive Distributions

Produce return level plots depicting prior and posterior predictive gev distributions.

rl.pred(post, qlim, npy, lh = c("gev", "gpd"), period = 1, lty = 1, col = 1,
xlab = "return period", ylab = "return level", ...)

`post`	A Markov chain generated using `posterior`, containing samples from the corresponding prior/posterior distribution.
`qlim`	A vector of length two, giving the limits for the quantiles at which the predictive probabilities are calculated.
`npy`	The Number of observation Per Year (in average). If “gev” likelihood, “npy” is supposed to be equal to 1 i.e. annual maxima.
`lh`	The likelihood.
`period`	A vector of integers. One curve is plotted for each element of `period`. The ith curve depicts the probabilities that that quantiles will be exceeded over the next `period[i]` periods.
`lty`	Passed to `matplot`.
`col`	Passed to `matplot`.
`xlab, ylab`	Labels for the x and y axes.
`...`	Other arguments passed to `matplot`.

See the user's guide.

The first two arguments to matplot are returned invisibly as a list.

If a linear trend on the location has been implemented, the plot corresponds to the distribution obtained when the trend parameter is zero.