Vinecop.pdf
- Vinecop.pdf(self, u: numpy.ndarray, num_threads: int = 1) numpy.ndarray
Evaluates the copula density.
The copula density is defined as joint density divided by marginal densities, irrespective of variable types.
When at least one variable is discrete, two types of “observations” are required in
u: the first \(n \; x \; d\)block contains realizations of \(F_{X_j}(X_j)\). The second \(n \; x \; d\)block contains realizations of \(F_{X_j}(X_j^-)\). The minus indicates a left-sided limit of the cdf. For, e.g., an integer-valued variable, it holds \(F_{X_j}(X_j^-) = F_{X_j}(X_j - 1)\). For continuous variables the left limit and the cdf itself coincide. Respective columns can be omitted in the second block.- Parameters:
- undarray, shape (n, m), dtype float
An \(n \times (d + k)\)or \(n \times 2d\)matrix of evaluation points, where \(k\)is the number of discrete variables (see
select()).- num_threadsint
The number of threads to use for computations; if greater than 1, the function will be applied concurrently to
num_threadsbatches ofu.
- Returns:
- ndarray, shape (n,), dtype float
A vector of length
ncontaining the copula density values.