GaussianConditionalIndependenceModel¶

class GaussianConditionalIndependenceModel(n_normal, normal_max_value, p_zeros, rhos, i_normal=None, i_ps=None)[source]¶

Bases: qiskit.aqua.components.uncertainty_models.multivariate_distribution.MultivariateDistribution

The Gaussian Conditional Independence Model for Credit Risk.

Dependency between individual risk variables and latent variable is approximated linearly.

Parameters

n_normal (int) – Number of qubits to represent the latent normal random variable Z
normal_max_value (float) – Min/max value to truncate the latent normal random variable Z
p_zeros (Union[List[float], ndarray]) – Standard default probabilities for each asset
rhos (Union[List[float], ndarray]) – Sensitivities of default probability of assets with respect to latent variable Z
i_normal (Union[List[float], ndarray, None]) – Indices of qubits to represent normal variable
i_ps (Union[List[float], ndarray, None]) – Indices of qubits to represent asset defaults

Methods

`build`
`build_controlled`	Adds corresponding controlled sub-circuit to given circuit
`build_controlled_inverse`	Adds controlled inverse of corresponding sub-circuit to given circuit
`build_controlled_inverse_power`	Adds controlled, inverse, power of corresponding circuit.
`build_controlled_power`	Adds controlled power of corresponding circuit.
`build_inverse`	Adds inverse of corresponding sub-circuit to given circuit
`build_inverse_power`	Adds inverse power of corresponding circuit.
`build_power`	Adds power of corresponding circuit.
`get_num_qubits`	returns number of qubits
`get_num_qubits_controlled`	returns number of qubits controlled
`pdf_to_probabilities`	pdf to probabilities
`required_ancillas`	returns required ancillas
`required_ancillas_controlled`	returns required ancillas controlled

Attributes