adelie.state.bvls#

adelie.state.bvls(X: MatrixNaiveBase32 | MatrixNaiveBase64, y_var: float, X_vars: ndarray, lower: ndarray, upper: ndarray, weights: ndarray, kappa: int, max_iters: int, tol: float, screen_set_size: int, screen_set: ndarray, is_screen: ndarray, active_set_size: int, active_set: ndarray, is_active: ndarray, beta: ndarray, resid: ndarray, grad: ndarray, loss: float)[source]#

Creates a BVLS state object.

Parameters:

X(n, p) Union[MatrixNaiveBase32, MatrixNaiveBase64]: Feature matrix. It is typically one of the matrices defined in adelie.matrix submodule.
y_varfloat: Variance of \(y\) equivalent to \(y^\top W y\).
X_vars(p,) ndarray: Variance of each column of X equivalent to \(\mathrm{diag}(X^\top W X)\).
lower(p,) ndarray: Lower bound for each variable.
upper(p,) ndarray: Upper bound for each variable.
weights(n,) ndarray: Observation weights.
kappaint: Violation batching size.
max_itersint: Maximum number of coordinate descents.
tolfloat: Coordinate descent convergence tolerance.
screen_set_sizeint: Number of screen groups. screen_set[i] is only well-defined for i in the range [0, screen_set_size).
screen_set(p,) ndarray: Screen set buffer. screen_set[i] is the i th screen variable that is in the range [0, p).
is_screen(p,) ndarray: Boolean vector indicating whether the j th feature is screen.
active_set_sizeint: Number of active groups. active_set[i] is only well-defined for i in the range [0, active_set_size).
active_set(p,) ndarray: Active set buffer. active_set[i] is the i th active variable that is in the range [0, p).
is_active(p,) ndarray: Boolean vector indicating whether the j th feature is active.
beta(p,) ndarray: Coefficient vector.
resid(n,) ndarray: Residual \(y-X\beta\).
grad(p,) ndarray: Internal buffer that is implementation-defined.
lossfloat: The current loss \(\frac{1}{2} \|y - X\beta\|_W^2\).

Returns:

wrap: Wrapper state object.