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Nonlinear Regression

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

Functions

`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)

Classes

`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
`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

Examples and How To

Desktop Workflow

Estimate Pharmacokinetic Parameters Using SimBiology Desktop

This example shows how to estimate one-compartment pharmacokinetic (PK) parameters given experimental drug concentration data.

STEP 1: Import and Explore Data
STEP 2: Create a PK Model
STEP 3: Fit Data

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 task in the SimBiology desktop.

Perform Data Fitting with PKPD 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.