xb calculates the linear prediction from the fitted model. That is, all
models can be thought of as estimating a set of parameters b1, b2,
..., bk, and the linear prediction is y = xb. For linear regression,
the values y are called the predicted values or, for out-of-sample
predictions, the forecast. For logit and probit, for example, y is
called the logit or probit index.
x1, x2, ..., xk are obtained from the data currently in memory and do
not necessarily correspond to the data on the independent variables
used to fit the model (obtaining the b1, b2, ..., bk).