gevrSeqTests: Sequential Tests for the GEVr Model
In eva: Extreme Value Analysis with Goodness-of-Fit Testing

Description Usage Arguments Details Value Examples

Sequentially performs the entropy difference (ED) test or the multiplier or parametric bootstrap score tests for the GEVr model.

gevrSeqTests(
  data,
  bootnum = NULL,
  method = c("ed", "pbscore", "multscore"),
  information = c("expected", "observed"),
  allowParallel = FALSE,
  numCores = 1
)

`data`	Data should be contain n rows, each a GEVr observation.
`bootnum`	If method equals 'pbscore' or 'multscore', the number of bootstrap simulations to use.
`method`	Which test to run: ED test (ed), multiplier (multscore) or parametric bootstrap (pbscore) score test.
`information`	To use expected (default) or observed information in the score tests.
`allowParallel`	If method equals 'pbscore', should the parametric boostrap procedure be run in parallel or not. Defaults to false.
`numCores`	If allowParallel is true, specify the number of cores to use.

GEVr data (in matrix x) should be of the form x[i,1] > x[i, 2] > \cdots > x[i, r] for each observation i = 1, …, n. See function ‘pSeqStop’ for details on transformed p-values.

Function returns a dataframe containing the test statistics, estimates, and p-value results of the sequential tests.

`r`	Value of r to be tested.
`p.values`	Raw p-values from the individual tests at each value of r.
`ForwardStop`	Transformed p-values according to the ForwardStop stopping rule.
`StrongStop`	Transformed p-values according to the StrongStop stopping rule.
`statistic`	Returned test statistics of each individual test.
`est.loc`	Estimated location parameter for the given r.
`est.scale`	Estimated scale parameter for the given r.
`est.shape`	Estimated shape parameter for the given r.

1 2	x <- rgevr(200, 5, loc = 0.5, scale = 1, shape = 0.25) gevrSeqTests(x, method = "ed")

  r  p.values ForwardStop StrongStop  statistic   est.loc est.scale est.shape
1 2 0.8800938   1.1925884  0.9685727 -0.1508503 0.5155469  1.021696 0.3374637
2 3 0.2428877   0.8831028  0.8057608 -1.1677994 0.5086324  1.051590 0.3369951
3 4 0.4527022   1.1855323  0.8132119 -0.7509176 0.5260023  1.062714 0.3098999
4 5 0.8293776   1.7683023  1.3489195 -0.2154999 0.5333976  1.061276 0.2967635