boot.matrix {extRemes} | R Documentation |
Set up matrices for bootstrapping sequences of extreme values.
boot.matrix(x, y)
x |
Output from decluster.runs or decluster.intervals . |
y |
Vector of observations. |
This function merely formats the information needed by boot.sequence
to improve efficiency.
A list containing two (unamed) matrices, each with columns corresponding to clusters identified in 'x.'
comp1 |
inter-exceedance times |
comp2 |
Data values in 'y' corresponding to the exceedances in each cluster. |
Maintained by Eric Gilleland.
Chris Ferro
boot.sequence
, decluster.intervals
, decluster.runs
# Simulate 1000 uniform random variables. x <- runif(1000) # Perform runs declustering with run length = 1 and 90th percentile as threshold. u <- quantile(x, 0.9) z <- x > u dec <- decluster.runs(z, 1) # Make sure estimated run length is not zero before doing the rest. if( dec[["par"]] != 0) { # Set up the matrices for bootstrapping. mat <- boot.matrix(dec, x) # Bootstrap with 500 iterations. eib <- numeric(500) for( i in 1:500) { set.seed(i) zb <- boot.sequence(mat[[1]],mat[[2]],u) > u eib[i] <- exi.intervals(zb) } # end of for 'i' loop. # Obtain bootstrapped 95th percentile confidence intervals. conf.int <- quantile( eib, c((1-0.95)/2,(1+0.95)/2)) } # end of if run length estimate not zero stmt.