`get_eta.Rd`

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)`

- 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.