Package: mapbayr 0.10.0

mapbayr: MAP-Bayesian Estimation of PK Parameters

Performs maximum a posteriori Bayesian estimation of individual pharmacokinetic parameters from a model defined in 'mrgsolve', typically for model-based therapeutic drug monitoring. Internally computes an objective function value from model and data, performs optimization and returns predictions in a convenient format. The performance of the package was described by Le Louedec et al (2021) <doi:10.1002/psp4.12689>.

Authors:Felicien Le Louedec [aut, cre], Kyle T Baron [ctb], Laura Morvan [ctb]

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mapbayr/json (API)
NEWS

# Install 'mapbayr' in R:
install.packages('mapbayr', repos = c('https://felicienll.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/felicienll/mapbayr/issues

Datasets:

On CRAN:

4.54 score 21 stars 33 scripts 240 downloads 38 exports 44 dependencies

Last updated 1 years agofrom:3ae0c72047. Checks:OK: 7. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 08 2024
R-4.5-winOKNov 08 2024
R-4.5-linuxOKNov 08 2024
R-4.4-winOKNov 08 2024
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R-4.3-macOKNov 08 2024

Exports:add_covariatesadm_cmtadm_linesadm_rowsaugmentbar_phicheck_mapbayr_modelcompute_ofvcompute_weightsdo_compute_ofvdo_mapbayr_simdo_model_averagingetaexdataexmodelfilterget_covget_dataget_etaget_paramget_phimapbayestmapbayr_plotmapbayr_vpcmbrestmerge_phimodel_averagingobs_cmtobs_linesobs_rowsparse_datehourplot_phipreprocess.ofv.fixpreprocess.ofv.idpreprocess.optimread_nmphisummarise_phiuse_posterior

Dependencies:BHclicolorspacecpp11crayondplyrfansifarvergenericsggplot2gluegtablehmsisobandlabelinglatticelifecyclemagrittrMASSMatrixmgcvmrgsolvemunsellnlmepillarpkgconfigprettyunitsprogresspurrrR6RColorBrewerRcppRcppArmadillorlangscalesstringistringrtibbletidyrtidyselectutf8vctrsviridisLitewithr

Readme and manuals

Help Manual

Help pageTopics
Add covariate columns to a datasetadd_covariates add_covariates.data.frame add_covariates.mrgmod
Add administration lines to a datasetadm_rows adm_rows.data.frame adm_rows.missing adm_rows.mrgmod
Return the mapbay_tab as a data.frameas.data.frame.mapbayests
Compute full PK profile prediction from mapbayr estimates.augment
Compute full PK profile prediction from mapbayr estimates.augment.mapbayests
Check if model is valid for 'mapbayr'check_mapbayr_model
Compute the objective function valuecompute_ofv do_compute_ofv
Data helpers: functions to build the datasetdata_helpers
Deprecated functionsadm_lines deprecations mbrest obs_lines
Simulate with mapbayrdo_mapbayr_sim
Estimation objectest001
Generate a vector of "ETA"eta
Example model and dataexdata exmodel exmodel_exdata
Filter a dataset within a mrgmodfilter.mrgmod
Get content from objectget_cov get_cov.mapbayests get_data get_data.mapbayests get_data.mrgmod get_eta get_eta.mapbayests get_param get_param.mapbayests get_phi get_phi.mapbayests get_x
Plot posterior distribution of bayesian estimateshist.mapbayests
Estimate parameters (maximum a posteriori)mapbayest
Make mapbayr plotmapbayr_plot
Visual Predicted Checksmapbayr_vpc
Average predictions from multiple modelscompute_weights do_model_averaging model_averaging
Add observation lines to a datasetobs_rows obs_rows.data.frame obs_rows.missing obs_rows.mrgmod
Parse value to "POSIXct"parse_datehour
Plot predictions from mapbayests objectplot.mapbayests
Preprocess model and data for ofv computationpreprocess.ofv preprocess.ofv.fix preprocess.ofv.id
Pre-process: arguments for optimization functionpreprocess.optim
Print a mapbayests objectprint.mapbayests
Use posterior estimationuse_posterior
Compare results to NONMEM .phibar_phi merge_phi plot_phi read_nmphi summarise_phi vs_nonmem
Read compartment options in a modeladm_cmt obs_cmt x_cmt