Description Usage Arguments Details Author(s) See Also Examples
View source: R/Take_expected_value.R
This function calculates the expected value of supremum for Wiener process, which is also known as
H_{λ}(S))=\mathbb{E}\exp(\sup(√{2}W_{t}-t))
1 2 | Take_expected_value(interval_end = 1, points = 100,
number_of_trajectories = 1000)
|
interval_end |
Describes the end of interval on which expression(H_\lambda(S)) should be calculated. Default is 1. |
points |
Tells on how many points should the maximum be estimated. Points are spread evenly. |
number_of_trajectories |
Determines the number of trajectory realizations on which the expected values is estimated by taking a mean of those realizations. |
Marcin ma mala palke
Marcin Kosi?ski, m.p.kosinski@gmail.com
Other Rpickands: Rpickands-package
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 | Take_expected_value(10,100,1000)
# Parallel computing
library(parallel)
cl <- makeCluster(detectCores())
clusterEvalQ(cl, library(Rpickands))
system.time({
m <- parLapply(cl, 1:100,Take_expected_value,
copy_number=100000,points=1000)
})
stopCluster(cl)
#####HUGE SIMULATION#####
m1 <- vector("list", 100)
library(parallel)
cl <- makeCluster(detectCores())
clusterEvalQ(cl, library(Rpickands))
system.time({
m1 <- parLapply(cl, 1:100,Take_expected_value, copy_number=100000,points=10000)
})
stopCluster(cl)
|
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