create.poped.database() now uses a better method of
identifying the total number of parameters of each type (bpop, d, sigma,
etc.) in a user defined model parameter function (the
ff_fun argument in create.poped.database())
(#73).
create.poped.database() has a new option
reorder_parameter_vectors, which is turned off by default.
When turned on, if you use named arguments in bpop or
d then PopED will try to figure out the order of the
parameters based on what is found in the fg_fun. See the
resulting poped_db$parameters and make sure the order
matches with fg_fun.
start_parallel() has a new default
fornum_cores, which is now one less than the number of
cores available from parallel::detectCores().
model_prediction() and therefore
plot_model_prediction() allow for log-normal distributions
when using the PI option. This makes sense if you expect the prediction
interval of the model will be approximately log-normally distributed,
which might often be the case in pop PK models. The new default is now
PI_ln_dist = TRUE.
poped_optim() now has an explicit argument allowing
for the specification of Ds-optimal parameters of interest. The option
is ds_index.
Minor bug fixes
Added the options allow_replicates=TRUE/FALSE,
allow_replicates_xt=TRUE/FALSE and
allow_replicates_a=TRUE/FALSE to poped_optim.
This allows the optimization algorithm to avoid replicates (or not) in
the design components. Currently only works for discrete variable
optimization. Future versions will also handle continuous
optimization.
Exported a function for the computation of the Bayesian Fisher
information matrix for individual parameters of a population model based
on Maximum A Posteriori (MAP) estimation of the empirical Bayes
estimates (EBEs) in a population model. See
?evaluate_fim_map for more details.
Allowing for no covariates in the function that automatically
builds a PopED parameter function from a model function
(?build_sfg).
Updates to documentation and package testing.
Minor bug fixes.
Added the ability to incorporate limit of quantification information into FIM calculations (both upper and lower limits). See the new vignette on the webpage https://andrewhooker.github.io/PopED/articles/handling_loq.html
Adding functionality to optimize groupsize and total size of the
study. See ?optimize_groupsize,
`?optimize_n_eff and ?optimize_n_rse. This is
also implemented in poped_optim through the
opt_inds=T argument.
Updating Vignettes, including a new one about using other tools to use as simulators for design computations. See https://andrewhooker.github.io/PopED/articles/model_def_other_pkgs.html
Simplify RxODE syntax in the above vingette (#47, @mattfidler).
Added the ability to predict and plot model prediction intervals
by computing the expected variance (using an FO approximation) and then
computing a prediction interval based on an assumption of normality. See
?model_prediciton and ?plot_model_prediction.
The computation is faster but less accurate compared to using
DV=TRUE (and groupsize_sim = 500) in the two
functions.
Named parameters are now passed to all calculations so that the FIM and RSE output is more readable with parameter names instead of default names.
Allow for parallel computation in
plot_efficiency_of_windows (#50).
Make parallelization work with mrgsolve on windows (#37, #45, #46, #51, @Vincent-AC).
Updated the function for automatic building of parameter model
function (see build_sfg).
Simplify derivative calculations (#34, @martin-gmx).
Allow for only simulating model_switch > 1 models.
Change the defult Ds calculation to be on log scale.
Updated the website at https://andrewhooker.github.io/PopED
Remove options for discontinued dplyr commands
rbind_all and rbind_list.
Minor bug fixes in shrinkage calculations (#44, #39, @martin-gmx).
New and improved vignettes (#30, @giulialestini)!
Added power evaluation script to test the power of a design to
identify a parameter different than an assumed value. The function also
calculates the number of individuals needed in a design to have a
specific power. See ?evaluate_power for more information
(#26, @martin-gmx).
Added function to compute expected shrinkage of a design. See
?shrinkage for more information.
Updated and added new example scripts in
system.file("examples", package="PopED") (). This includes
an example describing how to handle covariate distributions in optimal
design, an example on how to incorporate IOV, an example on how to
handle shrinkage, an example with a full covariance matrix and an
example with a prior FIM (#30, @giulialestini and @martin-gmx).
Major overhaul in optimization methods used in
poped_optim() so that generic optimization routines like
optim() can be easily used in optimizing PopED
designs.
Update speed of FIM calculations (#20, @martin-gmx).
Update RSE calculations so that prior FIM is handled correctly (#22, @martin-gmx).
Simplified code and removed duplicated code (#21, #24 and #32, @martin-gmx).
New ways of handling inverting matricies, should be faster and
work better when the matricies are ill-conditioned. See
?inv for more information (#19, @martin-gmx).
Updated functionality of IOV calculations.
Updates to optim_ARS() for when to stop
search.
Extended functionality of plot_model_prediction()
(#23, @martin-gmx).
Bug fixing. See https://github.com/andrewhooker/PopED/commits/master for more information.
Exported the summary method for the results of
poped_optim in the PopED NAMESPACE, so that the method can
actually be used! Just use summary(output).
Fixed some old bugs that used return as a varible in
functions, a la MATLAB.
Added a vignette to introduce PopED!
Improved optimization with poped_optim, plus all
example scripts now running with poped_optim.
Update to more easily allow discrete optimization of xt and a variables. See the example scripts.
Added a summary method for the results of
poped_optim. Just use
summary(output).
changed handling of seed numbers in optimizations.
more robust handling of non-population models
more natural handling of NA values in design vectors
NAMESPACE: removed ggplot2 from “Depends” and added to “Imports”
Added mean line to efficiency plots.
Update to computation and error handling for Laplace approximation to ED objective function.
Added more intuitive cost function input. See examples in
?poped_optim
Various small changes and bug fixes.
Added new optimization methods and tools, see
?poped_optim(). This function incorporates the new
optimization routines optim_ARS() and optim_LS
which are optimized versions of previous optimization algorithms used in
PopED. Both can be run with parallelization. poped_optim()
also incorporates the genetic algorithm from GA::ga(),
which can also be run with parallelization, and the “L-BFGS-B” method
from stats::optim(). poped_optim() should be
more efficient and faster than poped_optimize().
Changed the default objective function to be the log of the
determinant of the FIM.
create.poped.database(ofv_calc_type=4)
Various small changes and bug fixes.
Fixed plot_efficiency_of_windows() bug that had
wrong headers on each subplot.
Fixed bug in plot_model_prediction() that did not
plot the optimized design, but instead the initial design
Reorganized the database created from
create.poped.database(). The output from this function is
now a list with 5 sub-lists: design, design_space, model, parameters and
settings. Also removed duplicate entries in the database for easier
manipulation. This will cause some back compatibility issues when
referring to elements in a database.
Added example 10 describing a PKPD design of hepatitis C virus
(HCV) kinetics to the
system.file("examples",package="PopED") directory of the
PopED installation.
Updated model_prediction() to allow for creation of NONMEM
datasets.
Useful for testing of optimized designs via PsN’s (http://psn.sf.net)
SSE tool, for example.
Two new functions create_design() and create_design_space() that allow for design and design space creation without the need for a model or parameter values.
Updated the create.poped.database() function to use create_design() and create_design_space()
Added examples for evaluation and optimization of a one-target quasi-steady-state target mediated drug disposition model (TMDD) to the system.file(“examples”,package=“PopED”) directory of the PopED installation.
Added a 2-compartment, oral absorption, multiple dose example to the system.file(“examples”, package=“PopED”) directory of the PopED installation.
Updated plot_efficiency_of_windows() to allow for the plotting of the RSE of each parameter on the y-axis.
Updated error handing for the Laplace approximation of the ED OFV.
Fixed bug when computing FIM with only one BSV term present in model (calculation gave an error).
Fixed a bug in plot_model_predictions where an error was returned if not all time values in the xt matrix were to be used for the design calculation (ni is different from size(xt,2), see ?create_poped_database).
Various small bug fixes.
Updated package author list
New functionality to compute the ED OFV using the Laplace approximation. This can be orders of magnitude faster than the standard MC integration approach. See ‘?ed_laplace_ofv’ and ‘?evaluate.e.ofv.fim’
Added a general function to compute the FIM and OFV(FIM) for all available methods in PopED. See ‘?calc_ofv_and_fim’.
Added a general optimization algorithm ‘RS_opt_gen()’ that works for both D-family and E-family optimization.
Added optimization of E-family designs to ‘poped_optimize()’.
Changed distribution tests for package building
Fixed bug where correlations between BSV (between subject variability) terms in the model gave an error when creating a PopED database
Fixed a bug where get_rse failed when a parameter had a value of 3.