Equations (1.4) and (1.5) (or their transformed analogs) are to be solved for the vector s and sometimes the matrix B , to maximize the parameter likelihood function. As usual, it is equivalent and more convenient to minimize the negative of the log of the likelihood function. When the noise is normally distributed around zero, then within an inconsequential additive constant, the negative log likelihood is given by the familiar expression ( )