Parameter Estimation

Parameter estimation methods for process model identification.

Overview

Note

This section is currently under development. Complete implementation details will be available in a future release.

Parameter estimation techniques for determining optimal process parameters from experimental data.

Methods

• Least squares estimation

• Maximum likelihood estimation

• Bayesian parameter estimation

• Robust estimation methods

Implementation

# Implementation details coming soon
from sproclib.optimization import ParameterEstimator

# Basic usage example will be provided
pass

Applications

• Process model development

• Controller tuning

• Process monitoring

• Model validation