finalize.report is a secondary function called at the end of the
estimation runs. It outputs to the report file the final parameter estimates
for structural model parameters, residual variability and secondary parameters
as well as the related statistics (coefficients of variation, confidence
intervals, covariance and correlation matrix). finalize.report is
typically not called directly by users.
finalize.report(problem = NULL,
Fit = NULL,
files = NULL)Return a modified version of Fit, containing the following elements:
The vector of final parameter estimates.
The minimal value of the objective function.
The matrix of covariance for the parameter estimates.
A data.frame with the same structure as
problem$init but only containing the sorted estimated estimates.
The sorting is performed by order.param.list.
The upper triangle of the correlation matrix for the parameter estimates.
The coefficients of variations for the parameter estimates.
The confidence interval for the parameter estimates.
The Akaike Information Criterion.
A list of data related to the secondary parameters, containing the following elements:
A vector of secondary parameter estimates.
The matrix of covariance for the secondary parameter estimates.
The coefficients of variations for the secondary parameter estimates.
The confidence interval for the secondary parameter estimates.
A data.frame with the same structure as
problem$init but only containing the sorted fixed estimates.
The sorting is performed by order.param.list.
A data.frame with the same content as
problem$init but sorted by order.param.list.
A list containing the following levels:
A list containing as many levels as there are treatment levels
for the subject (or population) being evaluated, plus the trts
level listing all treatments for this subject (or population), and the
id level giving the identification number of the subject (or set to
1 if the analysis was run at the level of the population.
Each treatment-specific level is a list containing the following levels:
mij x 3 data.frame containing the times of observations of the dependent variables (extracted from the TIME variable), the indicators of the type of dependent variables (extracted from the CMT variable), and the actual dependent variable observations (extracted from the DV variable) for this particular treatment.
mij x c data.frame containing the times of observations of the dependent variables (extracted from the TIME variable) and all the covariates identified for this particular treatment.
bij x 4 data.frame providing the instantaneous inputs for a treatment and individual.
fij x (4+c) data.frame providing the zero-order inputs for a treatment and individual.
the particular treatment identifier.
A character string, indicating the scale of the analysis. Should be 'population' or 'subject'.
A data.frame of parameter data with the following columns: 'names', 'type', 'value', 'isfix', 'lb', and 'ub'.
Logical indicator of debugging mode.
Model function.
A list containing the following elements:
The vector of final parameter estimates.
The minimal value of the objective function.
The matrix of covariance for the parameter estimates.
A data.frame with the same structure as
problem$init but only containing the sorted estimated estimates.
The sorting is performed by order.param.list.
The upper triangle of the correlation matrix for the parameter estimates.
The coefficients of variations for the parameter estimates.
The confidence interval for the parameter estimates.
The Akaike Information Criterion.
A list of data related to the secondary parameters, containing the following elements:
The vector of secondary parameter estimates calculated using the initial estimates of the primary model parameters.
The vector of secondary parameter estimates calculated using the final estimates of the primary model parameters.
The vector of names of the secondary parameter estimates.
The matrix of partial derivatives for the secondary parameter estimates.
The matrix of covariance for the secondary parameter estimates.
The coefficients of variations for the secondary parameter estimates.
The confidence interval for the secondary parameter estimates.
A list of input used for the analysis. The following elements are expected and none of them could be null:
A .csv file located in the working directory, which contains
the dosing information, the observations of the dependent variable(s)
to be modeled, and possibly covariate information. The expected format
of this file is described in details in vignette('scaRabee',
package='scaRabee').
A .csv file located in the working directory, which contains
the initial guess(es) for the model parameter(s) to be optimized or used
for model simulation. The expected format of this file is described in
details in vignette('scaRabee',package='scaRabee').
A text file located in the working directory, which defines
the model. Models specified with explicit, ordinary or delay
differential equations are expected to respect a certain syntax and
organization detailed in vignette('scaRabee',package='scaRabee').
A .csv file reporting the values of the objective function and estimates of model parameters at each iteration.
A text file reporting for each individual in the dataset the final parameter estimates for structural model parameters, residual variability and secondary parameters as well as the related statistics (coefficients of variation, confidence intervals, covariance and correlation matrix).
A .csv file reporting the predictions and calculated residuals for each individual in the dataset.
A .csv file reporting the final parameter estimates for each individual in the dataset.
A .csv file reporting the simulated model predictions for each individual in the dataset. (Not used for estimation runs).
Sebastien Bihorel (sb.pmlab@gmail.com)
order.parms.list,