hidimstat.multivariate_1D_simulation

hidimstat.multivariate_1D_simulation(n_samples=100, n_features=500, support_size=10, sigma=1.0, rho=0.0, shuffle=True, seed=0)

Generate 1D data with Toeplitz design matrix

Parameters
n_samplesint

Number of samples.

n_featuresint

Number of features.

support_sizeint

Size of the support.

sigmafloat

Standard deviation of the additive White Gaussian noise.

rho: float

Level of correlation between neighboring features (if not shuffle).

shufflebool

Shuffle the features (breaking 1D data structure) if True.

seedint

Seed used for generating design matrix and noise.

Returns
Xndarray, shape (n_samples, n_features)

Design matrix.

yndarray, shape (n_samples,)

Target.

betandarray, shape (n_features,)

Parameter vector.

noisendarray, shape (n_samples,)

Additive white Gaussian noise.