CMA combination Step

Second CMA step: "glue" copulas and marginals into the same data structure.

cma_combination(x, cdf, copula)

Arguments

x	A rectangular (non-tidy) data structure with the sorted marginals (ascending order).
cdf	A rectangular (non-tidy) data structure with the CDF's.
copula	A rectangular (non-tidy) data structure with the copulas.

Value

A tabular (non-tidy) tibble with the joint scenarios.

See also

cma_separation

Examples

set.seed(123)

margins <- matrix(stats::rnorm(20), ncol = 2)
colnames(margins) <- c("a", "b")
probs   <- rep(1 / 10, 10)

# separate
sep <- cma_separation(x = margins, p = probs)
# combinate
comb <- cma_combination(margins, sep$cdf, sep$copula)

# The result is identical
margins # matrix
#>                 a          b
#>  [1,] -0.56047565  1.2240818
#>  [2,] -0.23017749  0.3598138
#>  [3,]  1.55870831  0.4007715
#>  [4,]  0.07050839  0.1106827
#>  [5,]  0.12928774 -0.5558411
#>  [6,]  1.71506499  1.7869131
#>  [7,]  0.46091621  0.4978505
#>  [8,] -1.26506123 -1.9666172
#>  [9,] -0.68685285  0.7013559
#> [10,] -0.44566197 -0.4727914
comb    # tibble
#> # A tibble: 10 × 2
#>          a      b
#>      <dbl>  <dbl>
#>  1 -0.560   1.22 
#>  2 -0.230   0.360
#>  3  1.56    0.401
#>  4  0.0705  0.111
#>  5  0.129  -0.556
#>  6  1.72    1.79 
#>  7  0.461   0.498
#>  8 -1.27   -1.97 
#>  9 -0.687   0.701
#> 10 -0.446  -0.473
all.equal(margins[ , "a"], comb$a)
#> [1] TRUE
all.equal(margins[ , "b"], comb$b)
#> [1] TRUE