 The AUTODIF Library automatically computes the derivatives of the objective function
with the same accuracy as the objective function itself and thereby
frees the developer from the onerous task of writing
and maintaining derivative code for statistical models.Equally important from the standpoint of model development,
the AUTODIF Library includes a "gradient stack", 
a quasi-Newton function minimizer, a derivative checker, and
container classes for vectors and matrices.The first application of the AUTODIF Library was published in 1992


The AUTODIF Library does not, however, completely liberate the developer from
writing all of the model constituents listed above.