LEDoptim                Optimization function for D-family, E-family
                        and Laplace approximated ED designs
RS_opt                  Optimize the objective function using an
                        adaptive random search algorithm for D-family
                        and E-family designs.
a_line_search           Optimize using line search
build_sfg               Build PopED parameter function from a model
                        function
calc_ofv_and_fim        Calculate the Fisher Information Matrix (FIM)
                        and the OFV(FIM) for either point values or
                        parameters or distributions.
cell                    Create a cell array (a matrix of lists)
create.poped.database   Create a PopED database
create_design           Create design variables for a full description
                        of a design.
create_design_space     Create design variables and a design space for
                        a full description of an optimization problem.
design_summary          Display a summary of output from poped_db
efficiency              Compute efficiency.
evaluate.e.ofv.fim      Evaluate the expectation of the Fisher
                        Information Matrix (FIM) and the expectation of
                        the OFV(FIM).
evaluate.fim            Evaluate the Fisher Information Matrix (FIM)
evaluate_design         Evaluate a design
evaluate_fim_map        Compute the Bayesian Fisher information matrix
evaluate_power          Power of a design to estimate a parameter.
feps.add                RUV model: Additive .
feps.add.prop           RUV model: Additive and Proportional.
feps.prop               RUV model: Proportional.
ff.PK.1.comp.oral.md.CL
                        Structural model: one-compartment, oral
                        absorption, multiple bolus dose, parameterized
                        using CL.
ff.PK.1.comp.oral.md.KE
                        Structural model: one-compartment, oral
                        absorption, multiple bolus dose, parameterized
                        using KE.
ff.PK.1.comp.oral.sd.CL
                        Structural model: one-compartment, oral
                        absorption, single bolus dose, parameterized
                        using CL.
ff.PK.1.comp.oral.sd.KE
                        Structural model: one-compartment, oral
                        absorption, single bolus dose, parameterized
                        using KE.
ff.PKPD.1.comp.oral.md.CL.imax
                        Structural model: one-compartment, oral
                        absorption, multiple bolus dose, parameterized
                        using CL driving an inhibitory IMAX model with
                        a direct effect.
ff.PKPD.1.comp.sd.CL.emax
                        Structural model: one-compartment, single bolus
                        IV dose, parameterized using CL driving an EMAX
                        model with a direct effect.
get_rse                 Compute the expected parameter relative
                        standard errors
mc_mean                 Compute the monte-carlo mean of a function
median_hilow_poped      Wrap summary functions from Hmisc and ggplot to
                        work with stat_summary in ggplot
model_prediction        Model predictions
ofv_criterion           Normalize an objective function by the size of
                        the FIM matrix
ofv_fim                 Evaluate a criterion of the Fisher Information
                        Matrix (FIM)
ones                    Create a matrix of ones
optim_ARS               Optimize a function using adaptive random
                        search.
optim_LS                Optimize a function using a line search
                        algorithm.
optimize_groupsize      Title Optimize the proportion of individuals in
                        the design groups
optimize_n_eff          Translate efficiency to number of subjects
optimize_n_rse          Optimize the number of subjects based on
                        desired uncertainty of a parameter.
pargen                  Parameter simulation
plot_efficiency_of_windows
                        Plot the efficiency of windows
plot_model_prediction   Plot model predictions
poped_gui               Run the graphical interface for PopED
poped_optim             Optimize a design defined in a PopED database
poped_optimize          Retired optimization module for PopED
shrinkage               Predict shrinkage of empirical Bayes estimates
                        (EBEs) in a population model
size                    Function written to match MATLAB's size
                        function
start_parallel          Start parallel computational processes
summary.poped_optim     Display a summary of output from poped_optim
tic                     Timer function (as in MATLAB)
toc                     Timer function (as in MATLAB)
zeros                   Create a matrix of zeros.
