# Population (and Individual) Optimal Experimental Design

## Documentation for package ‘PopED’ version 0.7.0

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

## Help Pages

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
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 | Create a matrix of ones
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.
optim_ARS | Optimize a function using adaptive random search.
optim_LS | Optimize a function using a line search algorithm.
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
RS_opt | Optimize the objective function using an adaptive random search algorithm for D-family and E-family designs.
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.