Regression and Data Fitting 

? 2008 Waterloo Maple Inc. 

Introduction 

 

This worksheet contains examples using the function LeastSquares from the "CurveFitting" package to perform linear, polynomial, and non-linear regression. It is important to load this package before you attempt to perform these calculations. The package has been loaded in the Startup Code (Edit>Startup Code). 

 

Defining the Data 

 

Create a set of data, X values and Y values, in separate lists: 

 

 

(2.1)

 

 

 

 

(2.2)

 

 

Linear Regression 

 

This example will fit a linear equation to the data represented. 

 

 

 

 

(3.1)

 

 

 

 

 

 

Polynomial Regression 

 

The mathematics below show examples using Maple for polynomial regression. An equation of a given form is produced for the data defined above and then plotted on a graph. 

 

 

 

(4.1)

 

 

 

 

 

 

 

 

(4.2)

 

 

 

 

 

 

 

Non-Linear Regression 

 

The following examples show how to fit non-linear equations to the data defined above. The equations will be of type logarithmic and exponential. 

 

 

(5.1)

 

 

 

 

 

 

 

(5.2)

 

 

 

 

 

 

NOTE: The previous examples illustrate Maple's built-in functional capabilities. However, it is important to note that Maple is a programming language and can be used to implement different algorithms or methods 

Legal Notice: The copyright for this application is owned by Maplesoft. The application is intended to demonstrate the use of Maple to solve a particular problem. It has been made available for product evalution purposes only and may not be used in any other context without the express permission of Maplesoft.