summary.ggevp: Summarizing Posterior Distribution with Parameters of GGEV

In MCMC4Extremes: Posterior Distribution of Extreme Value Models in R

Description

summary method for class "ggevp"

Usage

## S3 method for class 'ggevp'
summary(object, ...)

Arguments

object	an object of class "ggevp", usually, a result of a call to ggevp.
...	further arguments passed to or from other methods.

Value

The function summary.ggevp computes and returns a list of summary statistics of the posterior distribution given in object.

postmean	mean posterior
postmedian	median posterior
postCI	credibility interval
fitm	fit measures for standard GGEV model

References

Nascimento, F. F.; Bourguigon, M. ; Leao, J. S. (2015). Extended generalized extreme value distribution with applications in environmental data. HACET J MATH STAT.

See Also

ggevp

Examples

# Obtaining posterior distribution of a vector of simulated points
w=rggev(300,0.4,10,5,0.5)
# Obtaning 600 points of posterior distribution with delta=0.5
fit=ggevp(w,1,200,0.5)
a=summary(fit)

# Choice the best delta from a Grid of possible values as Nascimento et al. (2015)
## Not run: fitmeasures=summary(fit)$fitm
## Not run: delta=seq(0.1,2,0.2)
## Not run: results=array(0,c(length(delta),4))
## Not run: for (i in 1:length(delta))
## Not run:     {ajust=ggevp(w,1,200,delta[i])
## Not run:      results[i,]=summary(ajust)$fitm}

# As commented in Nascimento 2015 paper, a criteria to choice the best delta would be 
# create a grid of values of theta and choose the best according the lowest fit measures
## Not run: resultsb=cbind(delta,results)
## Not run: colnames(resultsb)=c("delta","AIC","BIC","pD","DIC")

MCMC4Extremes documentation built on May 1, 2019, 8:50 p.m.