Chapter 5: Q68E (page 235)
The formula for the matrix of an orthogonalprojection is derived in Exercise 67. Now considerthe QRfactorization of A, and express the matrixin terms of Q.
Short Answer
The equation holds.
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Chapter 5: Q68E (page 235)
The formula for the matrix of an orthogonalprojection is derived in Exercise 67. Now considerthe QRfactorization of A, and express the matrixin terms of Q.
The equation holds.
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Consider a consistent system .
(a) Show that this system has a solution in .
(b) Show that the system has only one solution in .
(c) If is the solution in androle="math" localid="1660124695419" is another solution of the system , show that . The vector is called the minimal solution of the linear system .
Consider an n x m matrix A with rank (A) = m. Is it always possible to write A as A = QL where Q is an n x m matrix with orthonormal columns and L is a lower triangular m x m matrix with positive diagonal entries? Explain.
Consider a symmetric matrix A. What is the relationship between Im(A)and ker(A)?
(a) Consider an matrix A such that . It is necessarily true that? Explain.
(b) Consider an matrix A such that . Is it necessarily true that ? Explain.
Find the least-squares line \(y = {\beta _0} + {\beta _1}x\) that best fits the data \(\left( { - 2,0} \right),\left( { - 1,0} \right),\left( {0,2} \right),\left( {1,4} \right),{\rm{ and }}\left( {2,4} \right)\), assuming that the first and last data points are less reliable. Weight them half as much as the three interior points.
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