Population (and Individual) Optimal Experimental Design


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Documentation for package ‘PopED’ version 0.3.2

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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
summary.poped_optim Display a summary of output from poped_optim
tic Timer function (as in MATLAB)
toc Timer function (as in MATLAB)
zeros Creates a matrix of zeros.