plot.gumbelp: Plot Fitted Gumbel Model

In MCMC4Extremes: Posterior Distribution of Extreme Value Models in R

Description

The plot method plot.gumbelp provides three differents plots: a histogram of the gumbel parameters, a plot of predictive density resulting of posterior distribution of gumbel parameters, and a return level plot of gumbel distribution.

Usage

## S3 method for class 'gumbelp'
plot(x, type = c("histogram", "predictive", "retlevel"), t=2, k=100, ...)

Arguments

x	a gumbelp object
type	which chosen plot
t	start return level
k	end return level
...	other graphics parameters

See Also

gumbelp

Examples

data(nidd.annual)
out=gumbelp(nidd.annual,1,500)
## Not run: plot(out,"histogram")
## Not run: plot(out,"predictive")
plot(out,"retlevel", 10)

Example output

Loading required package: evir
[1] 0.01333333
[1] 0.02666667
[1] 0.04
[1] 0.05333333
[1] 0.06666667
[1] 0.08
[1] 0.09333333
[1] 0.1066667
[1] 0.12
[1] 0.1333333
[1] 0.1466667
[1] 0.16
[1] 0.1733333
[1] 0.1866667
[1] 0.2
[1] 0.2133333
[1] 0.2266667
[1] 0.24
[1] 0.2533333
[1] 0.2666667
[1] 0.28
[1] 0.2933333
[1] 0.3066667
[1] 0.32
[1] 0.3333333
[1] 0.3466667
[1] 0.36
[1] 0.3733333
[1] 0.3866667
[1] 0.4
[1] 0.4133333
[1] 0.4266667
[1] 0.44
[1] 0.4533333
[1] 0.4666667
[1] 0.48
[1] 0.4933333
[1] 0.5066667
[1] 0.52
[1] 0.5333333
[1] 0.5466667
[1] 0.56
[1] 0.5733333
[1] 0.5866667
[1] 0.6
[1] 0.6133333
[1] 0.6266667
[1] 0.64
[1] 0.6533333
[1] 0.6666667
[1] 0.68
[1] 0.6933333
[1] 0.7066667
[1] 0.72
[1] 0.7333333
[1] 0.7466667
[1] 0.76
[1] 0.7733333
[1] 0.7866667
[1] 0.8
[1] 0.8133333
[1] 0.8266667
[1] 0.84
[1] 0.8533333
[1] 0.8666667
[1] 0.88
[1] 0.8933333
[1] 0.9066667
[1] 0.92
[1] 0.9333333
[1] 0.9466667
[1] 0.96
[1] 0.9733333
[1] 0.9866667
[1] 1
$retmedian
     50% 
207.0642 

$retpred
  [1]     -Inf 120.3677 144.7755 160.8419 172.4562 181.8021 189.5986 195.9927
  [9] 202.1499 207.0642 211.5225 215.8518 220.0537 223.6501 226.9027 229.8686
 [17] 232.7957 235.6725 238.2758 240.5826 242.7740 244.8609 246.9146 249.0027
 [25] 251.0243 252.8318 254.6256 256.3070 257.8729 259.3630 260.8033 262.2557
 [33] 263.7136 265.1274 266.4996 267.8325 269.1284 270.3496 271.5301 272.6802
 [41] 273.8017 274.8957 275.9637 277.0069 278.0499 279.0773 280.0823 281.0659
 [49] 282.0829 283.0792 284.0556 285.0128 285.9516 286.8209 287.6572 288.4784
 [57] 289.2787 290.0508 290.8268 291.6083 292.3768 293.1327 293.8527 294.5589
 [65] 295.2540 295.9385 296.6126 297.2766 297.9226 298.5562 299.1934 299.8618
 [73] 300.5208 301.1708 301.8120 302.4446 303.0690 303.6852 304.2935 304.8942
 [81] 305.4873 306.0731 306.6517 307.2234 307.7813 308.3237 308.8598 309.3898
 [89] 309.9137 310.4290 310.9338 311.4331 311.9243 312.4087 312.8812 313.3486
 [97] 313.8110 314.2688 314.7218 315.1703

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