IG Copula Family Functions
ig.Rd
Functions related to the IG copula family, denoted by 'ig'
.
Usage
pcondig21(v, u, theta, alpha)
qcondig21(p, u, theta, alpha)
qcondig(p, u, theta, alpha)
pcondig(v, u, theta, alpha)
pcondig12(u, v, theta, alpha)
qcondig12(p, v, theta, alpha)
dig(u, v, theta, alpha)
logdig(u, v, theta, alpha)
pig(u, v, theta, alpha)
rig(n, theta, alpha)
Arguments
- u, v
Vectors of values between 0 and 1 representing values of the first and second copula variables.
- theta
Parameter of the IG copula family. Vectorized; >0.
- alpha
Parameter of the IG copula family. Vectorized; >0.
- p
Vector of quantile levels between 0 and 1 to evaluate a quantile function at.
- n
Positive integer. Number of observations to randomly draw.
Note
Inputting two vectors greater than length 1 is allowed, if they're
the same length.
Also, qcondig21
and pcondig21
are the same as
qcondig
and pcondig
– they're the distributions of
variable 2 given 1.
Examples
u <- runif(10)
v <- runif(10)
pig(u, v, theta = 5, alpha = 1)
#> [1] 0.079648326 0.162368477 0.026362046 0.074323196 0.004455655 0.122812692
#> [7] 0.257811554 0.027490461 0.330950541 0.768651255
dig(u, v, theta = 2, alpha = 2)
#> [1] 0.6531305 0.8742874 0.9792254 1.1742052 1.2351493 0.9896548 0.9901719
#> [8] 1.0359737 0.8771307 1.6711461
logdig(u, v, theta = 2, alpha = 2)
#> [1] -0.425978390 -0.134346098 -0.020993430 0.160591535 0.211191866
#> [6] -0.010399079 -0.009876691 0.035341735 -0.131099211 0.513509688
pcondig21(v, u, theta = 3, alpha = 6)
#> [1] 0.91720529 0.17493670 0.03424133 0.32060350 0.40474305 0.19566369
#> [7] 0.40310912 0.06366146 0.38828096 0.96078162
qcondig21(v, u, theta = 3, alpha = 6)
#> [1] 0.83368782 0.17494456 0.03424133 0.32016882 0.39998875 0.19567598
#> [7] 0.40396967 0.06366146 0.38912428 0.98621554
pcondig12(u, v, theta = 3, alpha = 6)
#> [1] 0.078299811 0.834355112 0.600760902 0.158437311 0.007645536 0.466513005
#> [7] 0.501368832 0.289767791 0.734541432 0.704784075
qcondig12(u, v, theta = 3, alpha = 6)
#> [1] 0.083206392 0.834310960 0.600760870 0.155984470 0.007161119 0.466273968
#> [7] 0.494164675 0.289766698 0.731212224 0.824525886
rig(10, theta = 3, alpha = 3)
#> # A tibble: 10 × 2
#> u v
#> <dbl> <dbl>
#> 1 0.290 0.0312
#> 2 0.678 0.233
#> 3 0.735 0.318
#> 4 0.196 0.575
#> 5 0.981 0.533
#> 6 0.742 0.470
#> 7 0.0514 0.600
#> 8 0.530 0.944
#> 9 0.696 0.185
#> 10 0.689 0.224
# log density available for extra precision
log(dig(0.1, 0.1, 2.5, 12.3)) == logdig(0.1, 0.1, 2.5, 12.3)
#> [1] FALSE