MATLAB: How to perform nonlinear statistical analysis, or nonlinear regression analysis, using the Statistics Toolbox

Question

What functions are there in the Statistics Toolbox that I can use to perform nonlinear statistical analysis, or nonlinear regression analysis ?

Answer 1

The Statistics Toolbox has the following functions that support nonlinear fitting, prediction, confidence interval estimation, and multiple input interactive graphical exploration.:

nlinfit - Nonlinear least-squares fitting

nlintool - Prediction graph for nonlinear fits.

nlparci - Confidence intervals on parameters.

nlpredci - Confidence intervals for prediction.

nnls - Nonnegative least squares (in MATLAB).

treefit - Fit a tree-based model for classification or regression.

treeprune - Produce a sequence of subtrees by pruning.

treedisp - Show classification or regression tree graphically.

treetest - Compute error rate for tree.

treeval - Compute fitted value for decision tree applied to data.

For earlier versions, review the Nonlinear Models section of "help stats". You can find more information on the Statistics Toolbox, including a free trial version, at the following URL:

https://www.mathworks.com/products/statistics.html

You can also use the Curve Fitting Toolbox or the Optimization Toolbox for Nonlinear Analysis. For more information, see the following URL:

https://www.mathworks.com/discovery/data-fitting.html

(See the NonLinear Curve Fitting section)