| mxComputeNumericDeriv {OpenMx} | R Documentation |
For N free parameters, Richardson extrapolation requires (iterations * (N^2 + N)) function evaluations.
mxComputeNumericDeriv(freeSet = NA_character_, ..., fitfunction = "fitfunction", parallel = TRUE, stepSize = 1e-04, iterations = 4L, 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') |
parallel |
whether to evaluate the fitfunction in parallel (defaults to TRUE) |
stepSize |
starting set size (defaults to 0.0001) |
iterations |
number of Richardson extrapolation iterations (defaults to 4L) |
verbose |
Level of debugging output. |
The implementation is closely based on the numDeriv R package.
library(OpenMx) data(demoOneFactor) factorModel <- mxModel(name ="One Factor", mxMatrix(type = "Full", nrow = 5, ncol = 1, free = FALSE, values = .2, name = "A"), mxMatrix(type = "Symm", nrow = 1, ncol = 1, free = FALSE, values = 1 , name = "L"), mxMatrix(type = "Diag", nrow = 5, ncol = 5, free = TRUE , values = 1 , name = "U"), mxAlgebra(A %*% L %*% t(A) + U, name = "R"), mxExpectationNormal(covariance = "R", dimnames = names(demoOneFactor)), mxFitFunctionML(), mxData(cov(demoOneFactor), type = "cov", numObs = 500), mxComputeSequence( list(mxComputeNumericDeriv(), mxComputeReportDeriv()) ) ) factorModelFit <- mxRun(factorModel) factorModelFit$output$hessian