scipy.stats.random_correlation¶
- scipy.stats.random_correlation = <scipy.stats._multivariate.random_correlation_gen object>[source]¶
A random correlation matrix.
Return a random correlation matrix, given a vector of eigenvalues.
The eigs keyword specifies the eigenvalues of the correlation matrix, and implies the dimension.
- Parameters
- eigs1d ndarray
Eigenvalues of correlation matrix.
Notes
Generates a random correlation matrix following a numerically stable algorithm spelled out by Davies & Higham. This algorithm uses a single O(N) similarity transformation to construct a symmetric positive semi-definite matrix, and applies a series of Givens rotations to scale it to have ones on the diagonal.
References
- 1
Davies, Philip I; Higham, Nicholas J; “Numerically stable generation of correlation matrices and their factors”, BIT 2000, Vol. 40, No. 4, pp. 640 651
Examples
>>> from scipy.stats import random_correlation >>> rng = np.random.default_rng() >>> x = random_correlation.rvs((.5, .8, 1.2, 1.5), random_state=rng) >>> x array([[ 1. , -0.07198934, -0.20411041, -0.24385796], [-0.07198934, 1. , 0.12968613, -0.29471382], [-0.20411041, 0.12968613, 1. , 0.2828693 ], [-0.24385796, -0.29471382, 0.2828693 , 1. ]]) >>> import scipy.linalg >>> e, v = scipy.linalg.eigh(x) >>> e array([ 0.5, 0.8, 1.2, 1.5])
Methods
``rvs(eigs=None, random_state=None)``
Draw random correlation matrices, all with eigenvalues eigs.