Parameter estimation plays a critical role in accurately describing system behavior through mathematical models. Model examples include statistical probability distribution functions, parametric dynamic models, and data-based Simulink models. MathWorks products provide a broad range of parameter estimation capabilities.
Improving the accuracy of statistical models can involve estimating:
Statistics Toolbox™ supports these and similar parameter estimation tasks with more than 30 different probability distributions, including Normal, Weibull, Gamma, Generalized Pareto, and Poisson. The toolbox also supports linear and nonlinear regression.
Creating accurate parametric dynamic models can involve estimating:
System Identification Toolbox™ supports these tasks by providing parameter estimation capabilities for linear and nonlinear parametric dynamic models.
Common tasks for parameter estimation of Simulink models include:
Simulink Design Optimization™ supports these parameter estimation tasks with a Control and Estimation Tools Manager GUI that helps you configure, manipulate, and run your Simulink optimization problem.
Introduction to Simulink Design Optimization 52:00 (Webinar)