# Population (and Individual) Optimal Experimental Design

## Documentation for package ‘PopED’ version 0.3.1

- DESCRIPTION file.
- User guides, package vignettes and other documentation.
- Package NEWS.

## Help Pages

PopED-package | PopED - *Pop*ulation (and individual) optimal *E*xperimental *D*esign.
a_line_search | Optimize using line search
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 decription of an optimization problem.
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
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 absoprtion, multiple bolus dose, parameterized using CL driving an inhibitory IMAX model with a direct efect.
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 efect.
get_rse | Compute the expected parameter relative standard errors
LEDoptim | Optimization function for D-family, E-family and Laplace approximated ED designs
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 | Creates a matrix of ones
optim_ARS | Optimization Using Adaptive Random Search.
optim_LS | Optimization Using a Line Search Algorithm.
pargen | Parameter simulation
plot_efficiency_of_windows | Plot the efficiency of windows
plot_model_prediction | Plot model predictions
PopED | PopED - *Pop*ulation (and individual) optimal *E*xperimental *D*esign.
poped | PopED - *Pop*ulation (and individual) optimal *E*xperimental *D*esign.
poped_gui | Run the graphical interface for PopED
poped_optim | Optimization main module for PopED
poped_optimize | Optimization main module for PopED
RS_opt | Optimize the objective function using an adaptive random search algorithm for D-family designs.
RS_opt_gen | Optimize the objective function using an adaptive random search algorithm for D-family and E-family designs.
size | Function written to match MATLAB's size function
start_parallel | Start parallel computational processes
tic | Timer function (as in MATLAB)
toc | Timer function (as in MATLAB)
zeros | Creates a matrix of zeros.