Estimation

From the Algorithm pulldown, select the run method.

For population models, choose from:

Laplacian
QRPEM (Quasi-Random Parametric Expectation Maximization)
IT2S-EM (Iterated two-stage expectation-maximization)
Naive pooled

For individual models, choose from:

FOCE ELS (FOCE Extended Least Squares)
QRPEM (Quasi-Random Parametric Expectation Maximization)
Laplacian
FOCE L-B (First-Order Conditional Estimation, Lindstrom-Bates)
FO (First Order)
IT2S-EM (Iterated two-stage expectation-maximization)
Naive pooled

For more on run methods, see “Model engines” in the Phoenix NLME documentation.

Check the FOCEHess box to use FOCE Hessian. This option is available for Laplacian and IT2S-EM methods.
From the ODE Solver pulldown, select one of the ODE (ordinary differential equations) solver methods.

Matrix Exponent
Non-Stiff DVERK
Non-Stiff DOPRI5
Auto-Detect
Stiff

For more on ODE methodology, see “Differential equations in NLME” in the Phoenix NLME documentation.

Enter the Maximum Number of Iterations to use with each modeling run in the field.