Main Content

Nonlinear Regression

Least-squares estimation to fit grouped or pooled data, single or multiple experiments

Functions

fitPerform parameter estimation using SimBiology problem object
sbiofitPerform nonlinear least-squares regression
sbionlinfitPerform nonlinear least-squares regression using SimBiology models (requires Statistics and Machine Learning Toolbox software)
sbioparamestimPerform parameter estimation
sbiosampleparametersGenerate parameters by sampling covariate model (requires Statistics and Machine Learning Toolbox software)
sbiosampleerrorSample error based on error model and add noise to simulation data
sbioparameterciCompute confidence intervals for estimated parameters (requires Statistics and Machine Learning Toolbox)
sbiopredictionciCompute confidence intervals for model predictions (requires Statistics and Machine Learning Toolbox)

Objects

fitproblemSimBiology problem object for parameter estimation
groupedData Table-like collection of data and metadata
EstimatedInfo objectObject containing information about estimated model quantities
LeastSquaresResults objectResults object containing estimation results from least-squares regression
ObservableObject containing expression for post-simulation calculations
OptimResults objectEstimation results object, subclass of LeastSquaresResults
NLINResults objectEstimation results object, subclass of LeastSquaresResults
ParameterConfidenceIntervalObject containing confidence interval results for estimated parameters
PredictionConfidenceIntervalObject containing confidence interval results for model predictions

Apps

SimBiology Model BuilderBuild QSP, PK/PD, and mechanistic systems biology models interactively
SimBiology Model AnalyzerAnalyze QSP, PK/PD, and mechanistic systems biology models

Examples and How To

App Workflow

Programmatic Workflow

Concepts

  • Nonlinear Regression

    The purpose of regression models is to describe a response variable as a function of independent variables.

  • 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.

  • Progress Plot

    The progress plot provides the live feedback on the status of parameter estimation while using sbiofit, sbiofitmixed, or the Fit Data program in the SimBiology Model Analyzer app.