ggevp: Posterior Distribution with Parameters of Dual Gamma...

In MCMC4Extremes: Posterior Distribution of Extreme Value Models in R

Description

MCMC runs of posterior distribution of data with parameters of Dual Gamma Generalized Extreme Value Distribution density, with parameters mu, sigma and xi.

Usage

ggevp(data, block, int=1000, delta)

Arguments

data	data vector
block	the block size. A numeric value is interpreted as the number of data values in each successive block. All the data is used, so the last block may not contain block observations
int	Number of iteractions selected in MCMC. The program selects 1 in each 10 iteraction, then thin=10. The first thin*int/3 iteractions is used as burn-in. After that, is runned thin*int iteraction, in which 1 of thin is selected for the final MCMC chain, resulting the number of int iteractions.
delta	additional shape parameter of GGEV extension

Value

An object of class ggevp that gives a list containing the points of posterior distributions of mu, sigma and xi of the dual gamma generalized extreme value distribution, the data, mean posterior, median posterior and the credibility interval of the parameters.

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

plot.ggevp, summary.ggevp

Examples

# Obtaining posterior distribution of a vector of simulated points
w=rggev(300,0.1,10,5,0.5)

# Obtaning 500 points of posterior distribution with delta=0.5
ajust=ggevp(w,1,200,0.5)

Example output

Loading required package: evir
[1] 0.03333333
[1] 0.06666667
[1] 0.1
[1] 0.1333333
[1] 0.1666667
[1] 0.2
[1] 0.2333333
[1] 0.2666667
[1] 0.3
[1] 0.3333333
[1] 0.3666667
[1] 0.4
[1] 0.4333333
[1] 0.4666667
[1] 0.5
[1] 0.5333333
[1] 0.5666667
[1] 0.6
[1] 0.6333333
[1] 0.6666667
[1] 0.7
[1] 0.7333333
[1] 0.7666667
[1] 0.8
[1] 0.8333333
[1] 0.8666667
[1] 0.9
[1] 0.9333333
[1] 0.9666667
[1] 1

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