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.