MC.sim-methods | R Documentation |
MC.sim
~~Method to be invoked for running the Monte Carlo simulation. The simulator used is the method EmiStatR
from the homonym package. This method should be rewritted for working with another simulator.
MC.sim(x, EmiStatR.cores)
x |
an object of class |
EmiStatR.cores |
a |
A list
of length 2:
mc |
A |
sim1 |
A |
signature(x = "list", EmiStatR.cores = "numeric")
## the Monte Carlo simulation: MC.sim
library(EmiStatR)
data(P1)
P1 <- P1[165:(110*2),]
plot(P1[,2], typ="l")
library(stUPscales)
setting_EmiStatR <- setup(id = "MC_sim1",
nsim = 3, # use a larger number to have
# a proper confidence band of simulations
seed = 123,
mcCores = 1,
ts.input = P1,
rng = rng <- list(
qs = 150, # [l/PE/d]
CODs = c(pdf = "nor", mu = 4.378, sigma = 0.751), # log[g/PE/d]
NH4s = c(pdf = "nor", mu = 1.473, sigma = 0.410), # log[g/PE/d]
qf = 0.04, # [l/s/ha]
CODf = 0, # [g/PE/d]
NH4f = 0, # [g/PE/d]
CODr = c(pdf = "nor", mu = 3.60, sigma = 1.45), # 71 log[mg/l]
NH4r = 1, # [mg/l]
nameCSO = "E1", # [-]
id = 1, # [-]
ns = "FBH Goesdorf", # [-]
nm = "Goesdorf", # [-]
nc = "Obersauer", # [-]
numc = 1, # [-]
use = "R/I", # [-]
Atotal = 36, # [ha]
Aimp = c(pdf = "uni", min = 4.5, max = 25), # [ha]
Cimp = c(pdf = "uni", min = 0.25, max = 0.95), # [-]
Cper = c(pdf = "uni", min = 0.05, max = 0.60), # [-]
tfS = 1, # [time steps]
pe = 650, # [PE]
Qd = 5, # [l/s]
Dd = 0.150, # [m]
Cd = 0.18, # [-]
V = 190, # [m3]
lev.ini = 0.10, # [m]
lev2vol = list(lev = c(.06, 1.10, 1.30, 3.30), # [m]
vol = c(0, 31, 45, 190)) # [m3]
),
ar.model = ar.model <- list(
CODs = 0.5,
NH4s = 0.5,
CODr = 0.7),
var.model = var.model <- list(
inp = c("", ""), # c("CODs", "NH4s"), # c("", ""),
w = c(0.04778205, 0.02079010),
A = matrix(c(9.916452e-01, -8.755558e-05,
-0.003189094, 0.994553910), nrow=2, ncol=2),
C = matrix(c(0.009126591, 0.002237936,
0.002237936, 0.001850941), nrow=2, ncol=2)))
MC_setup <- MC.setup(setting_EmiStatR)
sims <- MC.sim(x = MC_setup, EmiStatR.cores = 0)
str(sims)
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