
IG Copula Family Functions
ig.RdFunctions 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