Population (and Individual) Optimal Experimental Design
Optimize using line search
Nonlinear minimization using BFGS with box constraints
Summarize your experiment for optimization routines
Result function for optimization routines
Header function for optimization routines
Summarize your optimization settings for optimization routines
Build PopED parameter function from a model function
Compute the autofocus portion of the stochastic gradient routine
Calculate the Fisher Information Matrix (FIM) and the OFV(FIM) for eit...
Compute an objective function and gradient
Create a cell array (a matrix of lists)
Create global variables in the PopED database
Create design variables and a design space for a full description of a...
Create design variables for a full description of a design.
Create a PopED database
Display a summary of output from poped_db
Function written to match MATLAB's diag function
D-family optimization function
Downsize a general design to a specific design
Trace optimization routines
Evaluate the expectation of determinant the Fisher Information Matrix ...
Evaluate the expectation of the Fisher Information Matrix (FIM) and th...
Compute efficiency.
Evaluate a design
Compute the Bayesian Fisher information matrix
Power of a design to estimate a parameter.
Evaluate the expectation of the Fisher Information Matrix (FIM) and th...
Evaluate the Fisher Information Matrix (FIM)
Extract a normalized group FIM
RUV model: Additive and Proportional.
RUV model: Additive .
RUV model: Proportional.
MATLAB feval function
Structural model: one-compartment, oral absorption, multiple bolus dos...
Structural model: one-compartment, oral absorption, multiple bolus dos...
Structural model: one-compartment, oral absorption, single bolus dose,...
Structural model: one-compartment, oral absorption, single bolus dose,...
Structural model: one-compartment, oral absorption, multiple bolus dos...
Structural model: one-compartment, single bolus IV dose, parameterized...
MATLAB fileparts function
Extract all model parameters from the PopED database.
Compute the expected parameter relative standard errors
Return all the unfixed parameters
Create a full D (between subject variability) matrix given a vector of...
Generate a random sample from a truncated normal distribution.
Model linearization with respect to epsilon.
Compute the inverse of a matrix
Function written to match MATLAB's isempty function
Optimization function for D-family, E-family and Laplace approximated ...
Model linearization with respect to epsilon.
Model linearization with respect to occasion variability parameters.
The linearized matrix L
Model linearization with respect to epsilon and eta.
Compute the natural log of the PDF for the parameters in an E-family d...
Compute the monte-carlo mean of a function
Wrap summary functions from Hmisc and ggplot to work with stat_summary...
The Fisher Information Matrix (FIM) for one individual
The full Fisher Information Matrix (FIM) for one individual Calculatin...
Modified Fedorov Exchange Algorithm
Evaluate the Fisher Information Matrix (FIM)
Model predictions
Normalize an objective function by the size of the FIM matrix
Evaluate a criterion of the Fisher Information Matrix (FIM)
Create a matrix of ones
Optimize a function using adaptive random search.
Optimize a function using a line search algorithm.
Title Optimize the proportion of individuals in the design groups
Translate efficiency to number of subjects
Optimize the number of subjects based on desired uncertainty of a para...
Parameter simulation
Plot the efficiency of windows
Plot model predictions
Run the graphical interface for PopED
Optimization main module for PopEDOptimize the objective function. The...
Optimization main module for PopED
Optimization main module for PopED
Optimize a design defined in a PopED database
Retired optimization module for PopED
PopED - Pop ulation (and individual) optimal E xperimental D esign.
Choose between arg1 and arg2
Function written to match MATLAB's rand function
Function written to match MATLAB's randn function
Optimize the objective function using an adaptive random search algori...
Predict shrinkage of empirical Bayes estimates (EBEs) in a population ...
Function written to match MATLAB's size function
Start parallel computational processes
Display a summary of output from poped_optim
Test to make sure that matricies are the right size
Timer function (as in MATLAB)
Timer function (as in MATLAB)
tryCatch both warnings (with value) and errors
Create a matrix of zeros.
Optimal experimental designs for both population and individual studies based on nonlinear mixed-effect models. Often this is based on a computation of the Fisher Information Matrix. This package was developed for pharmacometric problems, and examples and predefined models are available for these types of systems. The methods are described in Nyberg et al. (2012) <doi:10.1016/j.cmpb.2012.05.005>, and Foracchia et al. (2004) <doi:10.1016/S0169-2607(03)00073-7>.
Useful links