Nonlinear Regression

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

Functions

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)

Classes

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
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

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 a One-Compartment Model to an Individual's 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

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.

Perform Data Fitting with PK/PD Models

SimBiology lets you estimate model parameters by fitting the model to experimental time-course data, using either nonlinear regression or mixed-effects (NLME) techniques.