mxComputeNewtonRaphson: Optimize parameters using the Newton-Raphson algorithm
Description
This optimizer requires analytic 1st and 2nd derivatives of the
fit function. Comprehensive diagnostics are available by
increasing the verbose level.Usage
mxComputeNewtonRaphson(freeSet = NA_character_, ...,
fitfunction = "fitfunction", maxIter = 100L, tolerance = 1e-12,
verbose = 0L)
Arguments
freeSet
names of matrices containing free variables
...
Not used. Forces remaining arguments to be specified by name.
fitfunction
name of the fitfunction (defaults to 'fitfunction')
maxIter
maximum number of iterations
tolerance
optimization is considered converged when the maximum relative change in fit is less than tolerance
verbose
level of debugging output
References
Luenberger, D. G. & Ye, Y. (2008). Linear and nonlinear programming. Springer.