sbionlmefitsa
Estimate nonlinear mixed effects with stochastic EM algorithm (requires Statistics and Machine Learning Toolbox software)
sbionlmefitsa
will be removed in a future release. Use sbiofitmixed
instead.
Syntax
results
= sbionlmefitsa(modelObj
, pkModelMapObject
, pkDataObject
, InitEstimates
)
results
= sbionlmefitsa(modelObj
, pkModelMapObject
, pkDataObject
, CovModelObj
)
results
= sbionlmefitsa(..., Name,Value
)
results
= sbionlmefitsa(..., optionStruct
)
[results
, SimDataI
, SimDataP
]
= sbionlmefitsa(...)
Description
performs estimations using the Stochastic Approximation Expectation-Maximization (SAEM)
algorithm for fitting population data with the SimBiology® model, results
= sbionlmefitsa(modelObj
, pkModelMapObject
, pkDataObject
, InitEstimates
)modelObj
, and returns the estimated
results in the results
structure.
specifies the relationship between parameters and covariates using
results
= sbionlmefitsa(modelObj
, pkModelMapObject
, pkDataObject
, CovModelObj
)CovModelObj
, a CovariateModel
object.
The CovariateModel
object also provides the parameter
transformation.
performs estimations using the SAEM algorithm, with additional options specified by one
or more results
= sbionlmefitsa(..., Name,Value
)Name,Value
pair arguments.
Following is an alternative to the previous syntax:
specifies results
= sbionlmefitsa(..., optionStruct
)optionStruct
, a structure containing fields and
values, that are the name-value pair arguments accepted by nlmefitsa
.
The defaults for optionStruct
are the same as the defaults
for the name-value pair arguments used by nlmefitsa
, with the
exceptions explained in Input Arguments.
[
returns simulation data of the SimBiology model, results
, SimDataI
, SimDataP
]
= sbionlmefitsa(...)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
|
|
|
| Structure containing fields and values that are name-value pair arguments
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 = sbionlmefitsa(...,'Options',opt); % Perform data fitting Tip SimBiology software includes the |
Name-Value Arguments
Output Arguments
| Structure containing these fields:
|
|
|
|
|
Version History
Introduced in R2010a
See Also
Model object
| nlmefitsa
(Statistics and Machine Learning Toolbox) | PKData object
| SimData object
| PKModelDesign object
| PKModelMap object
| sbiofitstatusplot
| sbionlinfit
| sbionlmefit