Description Usage Arguments References Examples
Provides spatiotemporal correlation structure function based on Clayton copula. For more details on the parametric spatiotemporal correlation structures see section 2.3 and 2.4 in Papalexiou and Serinaldi (2020).
1 | stcfclayton(t, s, scfid, tcfid, copulaarg, scfarg, tcfarg)
|
t |
time lag |
s |
spatial lag (distance) |
scfid |
ID of the spatial (marginal) correlation structure (e.g. weibull) |
tcfid |
ID of the temporal (marginal) correlation structure (e.g. weibull) |
copulaarg |
parameter of the Clayton copula linking the marginal correlation structures |
scfarg |
parameters of spatial (marginal) correlation structure |
tcfarg |
parameters of temporal (marginal) correlation structure |
Papalexiou, S.M., Serinaldi, F. (2020). Random Fields Simplified: Preserving Marginal Distributions, Correlations, and Intermittency, With Applications From Rainfall to Humidity. Water Resources Research, 56(2), e2019WR026331, doi: 10.1029/2019WR026331
Papalexiou, S.M., Serinaldi, F., Porcu, E. (2021). Advancing Space-Time Simulation of Random Fields: From Storms to Cyclones and Beyond. Water Resources Research, 57, e2020WR029466, doi: 10.1029/2020WR029466
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 | library(plot3D)
## specify grid of spatial and temporal lags
d <- 31
st <- expand.grid(0:(d - 1),
0:(d - 1))
## get the STCS
wc <- stcfclayton(t = st[, 1],
s = st[, 2],
scfid = 'weibull',
tcfid = 'weibull',
copulaarg = 2,
scfarg = list(scale = 20,
shape = 0.7),
tcfarg = list(scale = 1.1,
shape = 0.8))
## visualize the STCS
wc.m <- matrix(wc,
nrow = d)
persp3D(z = wc.m, x = 1: nrow(wc.m), y = 1:ncol(wc.m),
expand = 1, main = "", scale = TRUE, facets = TRUE,
xlab="Time lag", ylab = "Distance", zlab = "STCF",
colkey = list(side = 4, length = 0.5), phi = 20, theta = 120,
resfac = 5, col= gg2.col(100))
|
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