Nonlinear Regression
Least-squares estimation to fit grouped or pooled data, single or
multiple experiments
Functions
fit | Perform parameter estimation using SimBiology problem object |
sbiofit | Perform nonlinear least-squares regression |
sbionlinfit | Perform nonlinear least-squares regression using SimBiology models (requires Statistics and Machine Learning Toolbox software) |
sbioparamestim | Perform parameter estimation |
sbiosampleparameters | Generate parameters by sampling covariate model (requires Statistics and Machine Learning Toolbox software) |
sbiosampleerror | Sample error based on error model and add noise to simulation data |
sbioparameterci | Compute confidence intervals for estimated parameters (requires Statistics and Machine Learning Toolbox) |
sbiopredictionci | Compute confidence intervals for model predictions (requires Statistics and Machine Learning Toolbox) |
Objects
fitproblem | SimBiology problem object for parameter estimation |
groupedData | Table-like collection of data and metadata |
EstimatedInfo object | Object containing information about estimated model quantities |
LeastSquaresResults object | Results object containing estimation results from least-squares regression |
Observable | Object containing expression for post-simulation calculations |
OptimResults object | Estimation results object, subclass of LeastSquaresResults |
NLINResults object | Estimation results object, subclass of LeastSquaresResults |
ParameterConfidenceInterval | Object containing confidence interval results for estimated parameters |
PredictionConfidenceInterval | Object containing confidence interval results for model predictions |
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
App Workflow
- Calculate NCA Parameters and Fit Model to PK/PD Data Using SimBiology Model Analyzer App
Perform noncompartmental analysis and calibrate model parameters by fitting to experimental PKPD data using nonlinear regression.
Programmatic Workflow
- Fit PK Parameters Using SimBiology Problem-Based Workflow
This example shows how to estimate model parameters using a SimBiology problem object. - Fit One-Compartment Model to Individual PK Profile
This example shows how to fit an individual's PK profile data to one-compartment model and estimate pharmacokinetic parameters. - Fit a Two-Compartment Model to PK Profiles of Multiple Individuals
This example shows how to estimate pharmacokinetic parameters of multiple individuals using a two-compartment model. - Estimate Category-Specific PK Parameters for Multiple Individuals
This example shows how to estimate category-specific (such as young versus old, male versus female in a hierarchical model), individual-specific, and population-wide parameters using PK profile data from multiple individuals. - Perform Hybrid Optimization Using sbiofit
This example shows how to configure sbiofit to perform a hybrid optimization.
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.