By Mathcad Staff
Least Squares Error
About this worksheet:
- Performs a weighted fit on a set of sample data by using the Least Squares Error method
- Applicable in academics and across all industries
- Performs sum of squares error function, least squares error, fitting function, and weighting function
This worksheet using PTC Mathcad shows you how to fit a set of sample data by using the Least Squares Error (LSE) method to minimize the sum of squares error function normalized by a weighting function.
This worksheet shows you how to create a sample data set and add some noise using the "rnd" function. By doing this you can create an unweighted fitting function. You can then define a weighted function which is used in the sum of squares error function, SS. You can use the "minimize" function to fit the unknown parameters and to minimize the SS error function.
Step by step notation, all sample data and solutions, and formulas and equations are provided as an example to aid you in solving.
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