Given x, coefficients and intercept, return linear predictions. Wrapper that works with both regular and sparse x. Only works for single set of coefficients and intercept.

get_eta(x, beta, a0)

Arguments

x

Input matrix, of dimension nobs x nvars; each row is an observation vector. If it is a sparse matrix, it is assumed to be unstandardized. It should have attributes xm and xs, where xm(j) and xs(j) are the centering and scaling factors for variable j respsectively. If it is not a sparse matrix, it is assumed to be standardized.

beta

Feature coefficients.

a0

Intercept.