More complicated examples include the derivative of a scalar function with respect to a matrix, known as the gradient matrix, which collects the derivative with respect to each matrix element in the corresponding position in the resulting matrix. In that case the scalar must be a function of each of the independent variables in the matrix. As another example, if we have an "n"-vector of dependent variables, or functions, of "m" independent variables we might consider the derivative of the dependent vector with respect to the independent vector. The result could be collected in an "m×n" matrix consisting of all of the possible derivative combinations. There are a total of nine possibilities using scalars, vectors, and matrices. Notice that as we consider higher numbers of components in each of the independent and dependent variables we can be left with a very large number of possibilities.