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.
results
= sbionlmefit(modelObj
, pkModelMapObject
, pkDataObject
, InitEstimates
)
results
= sbionlmefit(modelObj
, pkModelMapObject
, pkDataObject
, CovModelObj
)
results
= sbionlmefit(..., Name,Value
)
results
= sbionlmefit(..., optionStruct
)
[results
, SimDataI
, SimDataP
]
= sbionlmefit(...)
performs nonlinear mixedeffects 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 mixedeffects 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 namevalue 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.

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 namevalue pairs
accepted by the If you have Parallel Computing Toolbox™, you can enable parallel computing for faster data fitting by
setting the namevalue 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

Specify optional
commaseparated pairs of Name,Value
arguments. Name
is
the argument name and Value
is the corresponding value.
Name
must appear inside quotes. You can specify several name and value
pair arguments in any order as
Name1,Value1,...,NameN,ValueN
.
The sbionlmefit
function uses the namevalue pair arguments
supported by the nlmefit
function.
These nlmefit
namevalue pairs are hardcoded in
sbionlmefit
, and therefore, you cannot set them:
FEParamsSelect
FEConstDesign
FEGroupDesign
FEObsDesign
REConstDesign
REGroupDesign
REObsDesign
Vectorization
If you provide a CovariateModel
object as input to
sbionlmefit
, then these nlmefit
namevalue pairs are computed from the covariate model, and therefore, you cannot
set them:
FEGroupDesign
ParamTransform
REParamsSelect
You can set all other nlmefit
namevalue pairs. For details,
see the nlmefit
(Statistics and Machine Learning Toolbox) reference page.
Be aware that the defaults for these nlmefit
namevalue pairs
differ when used by sbionlmefit
:

Numeric array specifying the design matrix for each group. Default: 

Vector of integers specifying how the parameters are distributed. Note Do not use the Default: Vector of ones, which specifies all parameters are log transformed. 

Character vector specifying the optimization function used in maximizing the likelihood. Default: 

Structure containing multiple fields, including
Default: The default for 
Tip
SimBiology software includes the sbiofitstatusplot
function, which
you can specify in the OutputFcn
field of the
Options
namevalue pair input argument. This function
lets you monitor the status of fitting.
Tip
To simultaneously fit data from multiple dose levels, use the
InitEstimates
input argument and set the
REParamsSelect
namevalue pair input argument to a
1byn logical vector, with all entries set to
false
, where n equals the number of
fixed effects.

Structure containing these fields:





Model object
 PKData object
 PKModelDesign object
 PKModelMap object
 sbiofitstatusplot
 sbionlinfit
 sbionlmefitsa
 SimData object
 nlmefit
(Statistics and Machine Learning Toolbox)