MAP-Bayesian Estimation of PK Parameters

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Documentation for package ‘mapbayr’ version 0.5.0

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add_covariates Data helpers
add_covariates.mrgmod Add covariates columns to data
adm_0_cmt Get zero-order infusion compartment from mrgsolve model
adm_cmt Get administration compartment numbers from mrgsolve model
adm_lines Data helpers
adm_lines.mrgmod Add administrations lines to data
as.data.frame.mapbayests Return the mapbay_tab as a data.frame
augment Compute full PK profile prediction from mapbayr estimates.
augment.mapbayests Compute full PK profile prediction from mapbayr estimates.
check_mapbayr_model Check if model is valid for mapbayr
compute_ofv Compute the objective function value
data_helpers Data helpers
derivatives Compute the derivatives
get_data Get content from object
get_data.mapbayests Return data from a mapbayests
get_data.mrgmod Return data from a mrgmod
get_eta Get content from object
get_eta.mapbayests Return eta from a mapbayests
get_param Get content from object
get_param.mapbayests Return a posteriori param from a mapbayests
get_x Get content from object
hist.mapbayests Plot posterior distribution of bayesian estimates
mapbayest Estimate parameters (maximum a posteriori)
mbrest Estimate parameters (maximum a posteriori)
mbrlib Internal "mapbayr" model examples
obs_cmt Get observation compartment numbers from mrgsolve model
obs_lines Data helpers
obs_lines.mrgmod Add observations lines to data
plot.mapbayests Plot predictions from mapbayests object
postprocess Postprocess mapbayr
postprocess.optim Postprocess mapbayr
postprocess.output Postprocess mapbayr
preprocess.ofv Preprocess model and data for ofv computation
preprocess.ofv.fix Preprocess model and data for ofv computation
preprocess.ofv.id Preprocess model and data for ofv computation
preprocess.optim Pre-process: arguments for optimization function
print.mapbayests Print a mapbayests object
see_data Data helpers
use_posterior Use posterior param and covariates