| Contents | Index |
results = sbionlmefit(modelObj, pkModelMapObject, pkDataObject, InitEstimates)
results = sbionlmefit(modelObj, pkModelMapObject, pkDataObject, CovModelObj)
results = sbionlmefit(..., Name,Value)
results = sbionlmefit(..., optionStruct)
[results, SimDataI, SimDataP]
= sbionlmefit(...)
Note This function requires nlmefit in Statistics Toolbox (Version 7.0 or later). |
results = sbionlmefit(modelObj, pkModelMapObject, pkDataObject, InitEstimates) performs nonlinear mixed-effects estimation using the SimBiology model, modelObj, and returns estimated results in the results structure.
results = sbionlmefit(modelObj, pkModelMapObject, pkDataObject, CovModelObj) specifies the relationship between parameters and covariates using CovModelObj, a CovariateModel object. The CovariateModel object also provides the parameter transformation.
results = sbionlmefit(..., Name,Value) performs nonlinear mixed-effects estimation, with additional options specified by one or more Name,Value pair arguments.
Following is an alternative to the previous syntax:
results = sbionlmefit(..., optionStruct) specifies 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.
[results, SimDataI, SimDataP] = sbionlmefit(...) returns simulation data of the SimBiology model, modelObj, using the estimated values of the parameters.
modelObject |
SimBiology model object used to fit observed data. | |
pkModelMapObject |
PKModelMap object that defines the roles of the model components used for estimation. For details, see PKModelMap object.
| |
pkDataObject |
PKData object that defines the data to use in fitting, and the roles of the columns used for estimation. pkDataObject must define target data for at least two groups. For details, see PKData object.
| |
InitEstimates |
Vector of initial estimates for the fixed effects. The first P elements of InitEstimates correspond to the fixed effects for each P element of pkModelMapObject.Estimated. Additional elements correspond to the fixed effects for covariate factors. The first P elements of InitEstimates are transformed as specified by the ParamTransform name-value pairs (log transformed by default). For details on specifying initial estimates, see Setting Initial Estimates. | |
CovModelObj |
CovariateModel object that defines the relationship between parameters and covariates. For details, see CovariateModel object. | |
optionStruct |
Structure containing fields and values that are the name-value pairs accepted by the nlmefit function. The defaults for optionStruct are the same as the defaults for the arguments used by nlmefit, with the exceptions noted in Name-Value Pair Arguments.
|
Specify optional comma-separated pairs of Name,Value arguments, where Name is the argument name and Value is the corresponding value. Name must appear inside single quotes (' '). You can specify several name and value pair arguments in any order as Name1,Value1,...,NameN,ValueN.
The sbionlmefit function uses the name-value pair arguments supported by the nlmefit function.
These nlmefit name-value pairs are hard-coded 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 name-value pairs are computed from the covariate model, and therefore, you cannot set them:
FEGroupDesign
ParamTransform
REParamsSelect
You can set all other nlmefit name-value pairs. For details, see the nlmefit reference page.
Be aware that the defaults for these nlmefit name-value pairs differ when used by sbionlmefit:
'FEGroupDesign' |
Numeric array specifying the design matrix for each group. For details, see Specifying a Nonlinear, Mixed-Effects Model. Default: repmat(eye(P),[1 1 nGroups]), where P = the number of estimated parameters, and nGroups = the number of groups in the observed data. | |
'ParamTransform' |
Vector of integers specifying how the parameters are distributed. For details, see Specifying Parameter Transformations.
Default: Vector of ones, which specifies all parameters are log transformed. | |
'OptimFun' |
String specifying the optimization function used in maximizing the likelihood. Default: fminunc, if you have Optimization Toolbox™ installed. Otherwise, the default is fminsearch. | |
'Options' |
Structure containing multiple fields, including DerivStep, a scalar or vector specifying the relative difference used in the finite difference gradient calculation, and FunValCheck, a logical specifying whether to check for invalid values, such as NaN or Inf, from modelfun. Default: The default for DerivStep is the lesser of 1e-4, or the value of the SolverOptions.RelativeTolerance property of the configuration set associated with modelObj, with a minimum of eps^(1/3). The default for FunValCheck is off. |
Tip SimBiology software includes the sbiofitstatusplot function, which you can specify in the OutputFcn field of the Options name-value 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 name-value pair input argument to a 1-by-n logical vector, with all entries set to false, where n equals the number of fixed effects. |
results |
Structure containing these fields:
|
SimDataI |
SimData object containing data from simulating the model using the estimated parameter values for individuals. This object includes observed states and logged states. |
SimDataP |
SimData object containing data from simulating the model using the estimated parameter values for the population. This object includes observed states and logged states. |
Model object | nlmefit | PKCovariateModel object | PKData object | PKModelDesign object | PKModelMap object | sbiofitstatusplot | sbionlinfit | sbionlmefitsa | SimData object

See how to analyze, visualize, and model biological data and systems using MathWorks products.
Get free kit| © 1984-2012- The MathWorks, Inc. - Site Help - Patents - Trademarks - Privacy Policy - Preventing Piracy - RSS |