| mxComputeNewtonRaphson {OpenMx} | R Documentation |
This optimizer requires analytic 1st and 2nd derivatives of the fit function. Ramsay (1975) is used to speed convergence. Ramsay can be differentially applied to different groups of parameters. Comprehensive diagnostics are available by increasing the verbose level.
mxComputeNewtonRaphson(freeSet = NA_character_, ..., fitfunction = "fitfunction", maxIter = 100L, tolerance = 1e-12, verbose = 0L)
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 |
Luenberger, D. G. & Ye, Y. (2008). Linear and nonlinear programming. Springer.
Ramsay, J. O. (1975). Solving implicit equations in psychometric data analysis. Psychometrika, 40(3), 337-360.