Hessian and CRP Jacobian Scaling
The rows and columns of the Hessian and crossproduct Jacobian matrix
can be scaled when using the trustregion, NewtonRaphson, Double Dogleg,
and LevenbergMarquardt optimization techniques.
Each element G_{i,j}, i,j = 1, ... ,n, is divided by the
scaling factor d_{i} * d_{j}, where the scaling vector
d = (d_{1}, ... ,d_{n}) is iteratively updated in a way
specified by the HESCAL=i option, as follows:
 i = 0
 : No scaling is done (equivalent to d_{i}=1).

 : First iteration and each restart iteration sets:
 i = 1
 : refer to Mor (1978):
 i = 2
 : refer to Dennis, Gay, and Welsch (1981):
 i = 3
 : d_{i} is reset in each iteration:
where is the relative machine precision or, equivalently,
the largest double precision value that when added to 1 results in 1.
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