Th3HoopMan
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Could anybody link me to some good examples on how to go about doing them? I honestly have no idea how to go about doing these two types of problems.
This discussion focuses on QR decomposition using Householder and Givens transformations, specifically in the context of solving regression problems. QR decomposition is utilized to minimize residuals instead of forming normal equations, making it essential for linear least squares problems. A valuable resource provided is a lecture note from the University of Texas at Arlington, which includes examples and explanations relevant to the topic. The actual problem begins on page 11, with introductory material on pages 1-10.
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It's not clear what you are looking for here.Th3HoopMan said:Could anybody link me to some good examples on how to go about doing them? I honestly have no idea how to go about doing these two types of problems.
Examples of problems which can be solving using QRSteamKing said:It's not clear what you are looking for here.
Do you want to know how to develop QR decomposition using HH & Givens Transforms?
Or
Are you looking for examples of problems which can be solved using QR decomposition?
Just about any regression problem where the number of data points exceeds the degree of the curve being fitted.Th3HoopMan said:Examples of problems which can be solving using QR
Thank you!SteamKing said:Just about any regression problem where the number of data points exceeds the degree of the curve being fitted.
You use QR to find the minimum of the residuals in place of forming the normal equations.
Here is an example using linear least squares:
http://www.uta.edu/faculty/rcli/Teaching/math5392/NotesByHyvonen/lecture3.pdf
Note: actual problem starts on p. 11, but there is a good intro. in pp. 1-10.![]()