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The Least Squares Approximation is a examples-intensive concept. However, it can be solved using the following concise formulas:
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for system
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:<math>A\bold{x}=\bold{b},</math>
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:<math> {A^T(A\bold{\hat{x}} - \bold{b})} = 0,</math>
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which is equivalent to
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:<math> {A^TA\bold{\hat{x}}} = A^{T}\bold{b}.</math>
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'''NOTE:'''
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Thorough examples are available in the [[MA265]] textbook, Webassign problems, and Past Exam Archive. Most problems only deal with linear and parabolic fits.
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'''Main Reference'''
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----
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Kolman, B., & Hill, D. (2007). ''Elementary linear algebra with applications (9th ed.)''. Prentice Hall.
  
  

Latest revision as of 21:37, 4 March 2015

The Least Squares Solution



The Least Squares Approximation is a examples-intensive concept. However, it can be solved using the following concise formulas:

for system

$ A\bold{x}=\bold{b}, $
$ {A^T(A\bold{\hat{x}} - \bold{b})} = 0, $

which is equivalent to

$ {A^TA\bold{\hat{x}}} = A^{T}\bold{b}. $


NOTE:

Thorough examples are available in the MA265 textbook, Webassign problems, and Past Exam Archive. Most problems only deal with linear and parabolic fits.


Main Reference


Kolman, B., & Hill, D. (2007). Elementary linear algebra with applications (9th ed.). Prentice Hall.


Ryan Jason Tedjasukmana


Back to Inner Product Spaces and Orthogonal Complements

Back to MA265 Fall 2010 Prof Walther

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