sbionlmefit
Estimate nonlinear mixed effects using SimBiology models (requires Statistics and Machine Learning Toolbox software)
sbionlmefit
will be removed in a future release. Use sbiofitmixed
instead.
Syntax
results
= sbionlmefit(modelObj
, pkModelMapObject
, pkDataObject
, InitEstimates
)
results
= sbionlmefit(modelObj
, pkModelMapObject
, pkDataObject
, CovModelObj
)
results
= sbionlmefit(..., Name,Value
)
results
= sbionlmefit(..., optionStruct
)
[results
, SimDataI
, SimDataP
]
= sbionlmefit(...)
Description
performs nonlinear mixed-effects estimation using the SimBiology® model, results
= sbionlmefit(modelObj
, pkModelMapObject
, pkDataObject
, InitEstimates
)modelObj
, and returns estimated results
in the results
structure.
specifies the relationship between parameters and covariates using
results
= sbionlmefit(modelObj
, pkModelMapObject
, pkDataObject
, CovModelObj
)CovModelObj
, a CovariateModel
object.
The CovariateModel
object also provides the parameter
transformation.
performs nonlinear mixed-effects estimation, with additional options specified by one or
more results
= sbionlmefit(..., Name,Value
)Name,Value
pair arguments.
Following is an alternative to the previous syntax:
specifies results
= sbionlmefit(..., optionStruct
)optionStruct
, a structure containing fields and
values, that are the name-value pair arguments accepted by nlmefit
.
The defaults for optionStruct
are the same as the defaults
for the arguments used by nlmefit
, with the exceptions explained in
Input Arguments.
[
returns simulation data of the SimBiology model, results
, SimDataI
, SimDataP
]
= sbionlmefit(...)modelObj
, using the estimated values of
the parameters.
Input Arguments
| SimBiology model object used to fit observed data. |
|
Note If using a |
|
Note For each subset of data belonging to a single group (as defined in the
data column specified by the
|
| Vector of initial estimates for the fixed effects. The first
|
|
Tip To simultaneously fit data from multiple dose levels, omit the random
effect ( |
| Structure containing fields and values that are the name-value pairs
accepted by the If you have Parallel Computing Toolbox™, you can enable parallel computing for faster data fitting by
setting the name-value pair argument parpool; % Open a parpool for parallel computing opt = statset(...,'UseParallel',true); % Enable parallel computing results = sbionlmefit(...,'Options',opt); % Perform data fitting Tip SimBiology software includes the Tip To simultaneously fit data from multiple dose levels, use the
|
Name-Value Arguments
Output Arguments
| Structure containing these fields:
|
|
|
|
|
Version History
Introduced in R2009a
See Also
Model object
| nlmefit
(Statistics and Machine Learning Toolbox) | PKData object
| SimData object
| PKModelDesign object
| PKModelMap object
| sbiofitstatusplot
| sbionlinfit
| sbionlmefitsa