BiCopSim(N, family, par, par2 = 0, obj = NULL, check.pars = TRUE)N; defines the
bivariate copula family:
0 = independence copula
1 = Gaussian copula
2 = Student t copula (t-copula)
3 = Clayton copula
4 = Gumbel copula
5 = Frank copula
6 = Joe copula
7 = BB1 copula
8 = BB6 copula
9 = BB7 copula
10 = BB8 copula
13 = rotated Clayton copula (180 degrees; ``survival Clayton'')
14 = rotated Gumbel copula (180 degrees; ``survival Gumbel'')
16 = rotated Joe copula (180 degrees; ``survival Joe'')
17 = rotated BB1 copula (180 degrees; ``survival BB1'')
18 = rotated BB6 copula (180 degrees; ``survival BB6'')
19 = rotated BB7 copula (180 degrees; ``survival BB7'')
20 = rotated BB8 copula (180 degrees; ``survival BB8'')
23 = rotated Clayton copula (90 degrees)
24 = rotated Gumbel copula (90 degrees)
26 = rotated Joe copula (90 degrees)
27 = rotated BB1 copula (90 degrees)
28 = rotated BB6 copula (90 degrees)
29 = rotated BB7 copula (90 degrees)
30 = rotated BB8 copula (90 degrees)
33 = rotated Clayton copula (270 degrees)
34 = rotated Gumbel copula (270 degrees)
36 = rotated Joe copula (270 degrees)
37 = rotated BB1 copula (270 degrees)
38 = rotated BB6 copula (270 degrees)
39 = rotated BB7 copula (270 degrees)
40 = rotated BB8 copula (270 degrees)
104 = Tawn type 1 copula
114 = rotated Tawn type 1 copula (180 degrees)
124 = rotated Tawn type 1 copula (90 degrees)
134 = rotated Tawn type 1 copula (270 degrees)
204 = Tawn type 2 copula
214 = rotated Tawn type 2 copula (180 degrees)
224 = rotated Tawn type 2 copula (90 degrees)
234 = rotated Tawn type 2 copula (270 degrees) N; copula
parameter.N; second
parameter for bivariate copulas with two parameters (t, BB1, BB6, BB7, BB8,
Tawn type 1 and type 2; default: par2 = 0). par2 should be a
positive integer for the Students's t copula family = 2.BiCop object containing the family and parameter
specification.TRUE; if FALSE, checks
for family/parameter-consistency are ommited (should only be used with
care).N x 2 matrix of data simulated from the bivariate copula
with family and parameter(s) par, par2.
BiCop
object obj, the alternative version
BiCopSim(N, obj)can be used.
BiCop,
RVineSim
# simulate from a bivariate t-copula
simdata <- BiCopSim(100, 2, -0.7, par2 = 4)
# or alternatively
obj <- BiCop(family = 2, par = -0.7, par2 = 4)
simdata2 <- BiCopSim(100, obj)
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