step¶

hyppo.tools.step(n, p, noise=False, low=- 1, high=1)¶

Step simulation.

Step \((X, Y) \in \mathbb{R}^p \times \mathbb{R}\):

\[\begin{split}X &\sim \mathcal{U}(-1, 1)^p \\ Y &= \mathbb{1}_{w^T X > 0} + \epsilon\end{split}\]

where \(\mathbb{1}\) is the indicator function.

Parameters

n (int) -- The number of samples desired by the simulation (>= 5).
p (int) -- The number of dimensions desired by the simulation (>= 1).
noise (bool, default: False) -- Whether or not to include noise in the simulation.
low (float, default: -1) -- The lower limit of the uniform distribution simulated from.
high (float, default: 1) -- The upper limit of the uniform distribution simulated from.

Returns

x,y (ndarray of float) -- Simulated data matrices. x` and ``y have shapes (n, p) and (n, 1) where n is the number of samples and p is the number of dimensions.

joint_normal

quadratic