solve_quantile_regression

pyapprox.optimization.solve_quantile_regression(tau, samples, values, eval_basis_matrix, normalize_vals=False, opts={})

Solve quantile regression problems.

Parameters:

taufloat

The quantile in [0, 1)

samplesnp.ndarary (nvars, nsamples)

The training samples

valuesnp.ndarary (nsamples, 1)

The function values at the training samples

eval_basis_matrixcallable

A function returning the basis evaluated at the set of samples with signature eval_basis_matrix(samples) -> np.ndarray (nsamples, nbasis)

normalize_valsboolean

True - normalize the training values False - use the raw training values