pred {extrememix}R Documentation

Predictive Distribution

Description

Plot of the predictive distribution of an extreme value mixture model.

Usage

pred(x, ...)

## S3 method for class 'evmm'
pred(
  x,
  x_axis = seq(min(x$data), max(x$data), length.out = 1000),
  cred = 0.95,
  xlim = c(min(x$data), max(x$data)),
  ylim = NULL,
  ...
)

Arguments

x

the output of a model estimated with extrememix.

...

additional arguments for compatibility.

x_axis

vector of points where to estimate the predictive distribution.

cred

amplitude of the posterior credibility interval.

xlim

limits of the x-axis.

ylim

limits of the y-axis.

Details

Consider an extreme value mixture model f(y|\theta) and suppose a sample (\theta^{(1)},\dots,\theta^{(S)}) from the posterior distribution is available. The predictive distribution at the point y is estimated as

\frac{1}{S}\sum_{s=1}^Sf(y|\theta^{(s)})

Value

A plot of the estimate of the predictive distribution together with the data histogram.

References

do Nascimento, Fernando Ferraz, Dani Gamerman, and Hedibert Freitas Lopes. "A semiparametric Bayesian approach to extreme value estimation." Statistics and Computing 22.2 (2012): 661-675.

Examples

pred(rainfall_ggpd)


[Package extrememix version 0.0.1 Index]