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 |
... |
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)