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Nonlinear Mixed-Effects Modeling

Maximum likelihood estimation of population parameters

Functions

`fit`	Perform parameter estimation using SimBiology problem object
`sbiofitmixed`	Fit nonlinear mixed-effects model (requiresStatistics and Machine Learning Toolboxsoftware)
`sbionlmefit`	Estimate nonlinear mixed effects usingSimBiologymodels (requiresStatistics and Machine Learning Toolboxsoftware)
`sbionlmefitsa`	Estimate nonlinear mixed effects with stochastic EM algorithm (requiresStatistics and Machine Learning Toolboxsoftware)
`sbiosampleparameters`	Generate parameters by sampling covariate model (requiresStatistics and Machine Learning Toolboxsoftware)
`sbiosampleerror`	基于误差模型和添加噪声样本误差simulation data
`sbiofitstatusplot`	Plot status of nonlinear mixed-effects estimation

Objects

`fitproblem`	SimBiology problem object for parameter estimation
`CovariateModel object`	Define relationship between parameters and covariates
`groupedData`	Table-like collection of data and metadata
`EstimatedInfo object`	Object containing information about estimated model quantities
`Observable`	Object containing expression for post-simulation calculations
`NLMEResults object`	Results object containing estimation results from nonlinear mixed-effects modeling

Apps

SimBiology Model Builder	Build QSP, PK/PD, and mechanistic systems biology models interactively
SimBiology Model Analyzer	Analyze QSP, PK/PD, and mechanistic systems biology models

Examples and How To

Modeling the Population Pharmacokinetics of Phenobarbital in Neonates
This example shows how to build a simple nonlinear mixed-effects model from clinical pharmacokinetic data.
Fit PK Parameters Using SimBiology Problem-Based Workflow
This example shows how to estimate model parameters using a SimBiology problem object.

Concepts

Nonlinear Mixed-Effects Modeling
A mixed-effects model is a statistical model that incorporates bothfixed effectsandrandom effects.
Supported Methods for Parameter Estimation in SimBiology
SimBiology^®supports a variety of optimization methods for least-squares and mixed-effects estimation problems.
Error Models
SimBiology supports the error models described in the following table.