In Exercises 7–10, let\[W\]be the subspace spanned by the\[{\bf{u}}\]’s, and write y as the sum of a vector in\[W\]and a vector orthogonal to\[W\].

8.\[y = \left[ {\begin{aligned}{ - 1}\\4\\3\end{aligned}} \right]\],\[{{\bf{u}}_1} = \left[ {\begin{aligned}1\\1\\{\bf{1}}\end{aligned}} \right]\],\[{{\bf{u}}_2} = \left[ {\begin{aligned}{ - 1}\\3\\{ - 2}\end{aligned}} \right]\]

Short Answer

Expert verified

The vector\[{\bf{y}}\]is the sum of the vectors in\[W\]as\[{\bf{\hat y}} + {\bf{z}} = \left[ {\begin{aligned}{\frac{3}{2}}\\{\frac{7}{2}}\\1\end{aligned}} \right] + \left[ {\begin{aligned}{ - \frac{5}{2}}\\{\frac{1}{2}}\\2\end{aligned}} \right]\].

A vector orthogonal to \[W\] is \[\left[ {\begin{aligned}{ - \frac{5}{2}}\\{\frac{1}{2}}\\2\end{aligned}} \right]\].

Step by step solution

01

Write the definition

Orthogonal set: If \[{{\bf{u}}_i} \cdot {{\bf{u}}_j} = 0\] for \[i \ne j\], then the set of vectors \[\left\{ {{{\bf{u}}_1}, \ldots ,{{\bf{u}}_p}} \right\} \in {\mathbb{R}^n}\] is said to be orthogonal.

02

Check the set of given vectors is orthogonal or not

Given vectors are,\[{{\bf{u}}_1} = \left[ {\begin{aligned}1\\1\\1\end{aligned}} \right]\]and\[{{\bf{u}}_2} = \left[ {\begin{aligned}{ - 1}\\3\\{ - 2}\end{aligned}} \right]\].

Find the product\[{{\bf{u}}_1} \cdot {{\bf{u}}_2}\].

\[\begin{aligned}{{\bf{u}}_1} \cdot {{\bf{u}}_2} &= \left[ {\begin{aligned}1\\1\\1\end{aligned}} \right] \cdot \left[ {\begin{aligned}{ - 1}\\3\\{ - 2}\end{aligned}} \right]\\ &= 1\left( { - 1} \right) + 1\left( 3 \right) + 1\left( { - 2} \right)\\ &= 0\end{aligned}\]

As \[{{\bf{u}}_1} \cdot {{\bf{u}}_2} = 0\], so the set of vectors \[\left\{ {{{\bf{u}}_1},{{\bf{u}}_2}} \right\}\] is orthogonal.

03

The Orthogonal Decomposition Theorem

If \[\left\{ {{{\bf{u}}_1}, \ldots ,{{\bf{u}}_p}} \right\}\] is any orthogonal basis of \[w\], then \[{\bf{\hat y}} = \frac{{{\bf{y}} \cdot {{\bf{u}}_1}}}{{{{\bf{u}}_1} \cdot {{\bf{u}}_1}}}{{\bf{u}}_1} + \cdots + \frac{{{\bf{y}} \cdot {{\bf{u}}_p}}}{{{{\bf{u}}_p} \cdot {{\bf{u}}_p}}}{{\bf{u}}_p}\], where \[w\] is a subspace of \[{\mathbb{R}^n}\] and \[{\bf{\hat y}} \in w\], for which every \[{\bf{y}}\] can be written as \[{\bf{y}} = {\bf{\hat y}} + {\bf{z}}\] when \[{\bf{z}} \in {w^ \bot }\].

04

Find the Orthogonal projection of \[{\bf{y}}\] onto Span \[\left\{ {{{\bf{u}}_1},{{\bf{u}}_2}} \right\}\]

Find\[{\bf{y}} \cdot {{\bf{u}}_1}\],\[{\bf{y}} \cdot {{\bf{u}}_2}\],\[{{\bf{u}}_1} \cdot {{\bf{u}}_1}\]and\[{{\bf{u}}_2} \cdot {{\bf{u}}_2}\]first, where\[{\bf{y}} = \left[ {\begin{aligned}{ - 1}\\4\\3\end{aligned}} \right]\].

\[\begin{aligned}{\bf{y}} \cdot {{\bf{u}}_1} &= \left[ {\begin{aligned}{ - 1}\\4\\3\end{aligned}} \right] \cdot \left[ {\begin{aligned}1\\1\\1\end{aligned}} \right]\\ &= \left( { - 1} \right)\left( 1 \right) + 4\left( 1 \right) + 3\left( 1 \right)\\ &= 6\end{aligned}\]

\[\begin{aligned}{\bf{y}} \cdot {{\bf{u}}_2} &= \left[ {\begin{aligned}{ - 1}\\4\\3\end{aligned}} \right] \cdot \left[ {\begin{aligned}{ - 1}\\3\\{ - 2}\end{aligned}} \right]\\ &= \left( { - 1} \right)\left( { - 1} \right) + 4\left( 3 \right) + 3\left( { - 2} \right)\\ &= 7\end{aligned}\]

\[\begin{aligned}{{\bf{u}}_1} \cdot {{\bf{u}}_1} &= \left[ {\begin{aligned}1\\1\\1\end{aligned}} \right] \cdot \left[ {\begin{aligned}1\\1\\1\end{aligned}} \right]\\ &= 1\left( 1 \right) + \left( 1 \right)\left( 1 \right) + \left( 1 \right)\left( 1 \right)\\ &= 3\end{aligned}\]

\[\begin{aligned}{{\bf{u}}_2} \cdot {{\bf{u}}_2} &= \left[ {\begin{aligned}{ - 1}\\3\\{ - 2}\end{aligned}} \right] \cdot \left[ {\begin{aligned}{ - 1}\\3\\{ - 2}\end{aligned}} \right]\\ &= - 1\left( { - 1} \right) + \left( 3 \right)\left( 3 \right) + \left( { - 2} \right)\left( { - 2} \right)\\ &= 14\end{aligned}\]

Now, find the projection of\[{\bf{y}}\]onto Span\[\left\{ {{{\bf{u}}_1},{{\bf{u}}_2}} \right\}\]by substituting the obtained values into\[{\bf{\hat y}} = \frac{{{\bf{y}} \cdot {{\bf{u}}_1}}}{{{{\bf{u}}_1} \cdot {{\bf{u}}_1}}}{{\bf{u}}_1} + \cdots + \frac{{{\bf{y}} \cdot {{\bf{u}}_p}}}{{{{\bf{u}}_p} \cdot {{\bf{u}}_p}}}{{\bf{u}}_p}\]

\[\begin{aligned}{\bf{\hat y}} &= \frac{6}{3}{{\bf{u}}_1} + \frac{7}{{14}}{{\bf{u}}_2}\\ &= 2\left[ {\begin{aligned}1\\1\\1\end{aligned}} \right] + \frac{1}{2}\left[ {\begin{aligned}{ - 1}\\3\\{ - 2}\end{aligned}} \right]\\ &= \left[ {\begin{aligned}{\frac{3}{2}}\\{\frac{7}{2}}\\1\end{aligned}} \right]\end{aligned}\]

Hence, \[{\bf{\hat y}} = \left[ {\begin{aligned}{\frac{3}{2}}\\{\frac{7}{2}}\\1\end{aligned}} \right]\].

05

Find a vector orthogonal to \[W\]

Find\[{\bf{z}}\], which is orthogonal to\[W\]by using\[{\bf{z}} = {\bf{y}} - {\bf{\hat y}}\].

\[\begin{aligned}{\bf{z}} = {\bf{y}} - {\bf{\hat y}}\\ &= \left[ {\begin{aligned}{ - 1}\\4\\3\end{aligned}} \right] - \left[ {\begin{aligned}{\frac{3}{2}}\\{\frac{7}{2}}\\1\end{aligned}} \right]\\ &= \left[ {\begin{aligned}{ - \frac{5}{2}}\\{\frac{1}{2}}\\2\end{aligned}} \right]\end{aligned}\]

So,\[{\bf{z}} = \left[ {\begin{aligned}{ - \frac{5}{2}}\\{\frac{1}{2}}\\2\end{aligned}} \right]\].

06

Write \[y\] as a sum of a vector in \[W\]

Write\[{\bf{y}} = {\bf{\hat y}} + {\bf{z}}\], where\[{\bf{\hat y}} \in w\]and\[{\bf{z}} \in {w^ \bot }\].

\[\begin{aligned}{\bf{y}} &= {\bf{\hat y}} + {\bf{z}}\\ &= \left[ {\begin{aligned}{\frac{3}{2}}\\{\frac{7}{2}}\\1\end{aligned}} \right] + \left[ {\begin{aligned}{ - \frac{5}{2}}\\{\frac{1}{2}}\\2\end{aligned}} \right]\end{aligned}\]

Hence, \[{\bf{y}}\] as the sum of a vector in \[W\] is \[{\bf{\hat y}} + {\bf{z}} = \left[ {\begin{aligned}{\frac{3}{2}}\\{\frac{7}{2}}\\1\end{aligned}} \right] + \left[ {\begin{aligned}{ - \frac{5}{2}}\\{\frac{1}{2}}\\2\end{aligned}} \right]\].

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Most popular questions from this chapter

In Exercises 1-6, the given set is a basis for a subspace W. Use the Gram-Schmidt process to produce an orthogonal basis for W.

6. \(\left( {\begin{aligned}{{}}3\\{ - 1}\\2\\{ - 1}\end{aligned}} \right),\left( {\begin{aligned}{{}}{ - 5}\\9\\{ - 9}\\3\end{aligned}} \right)\)

Suppose \(A = QR\), where \(R\) is an invertible matrix. Showthat \(A\) and \(Q\) have the same column space.

Question: In Exercises 1 and 2, you may assume that\(\left\{ {{{\bf{u}}_{\bf{1}}},...,{{\bf{u}}_{\bf{4}}}} \right\}\)is an orthogonal basis for\({\mathbb{R}^{\bf{4}}}\).

2.\({{\bf{u}}_{\bf{1}}} = \left[ {\begin{aligned}{\bf{1}}\\{\bf{2}}\\{\bf{1}}\\{\bf{1}}\end{aligned}} \right]\),\({{\bf{u}}_{\bf{2}}} = \left[ {\begin{aligned}{ - {\bf{2}}}\\{\bf{1}}\\{ - {\bf{1}}}\\{\bf{1}}\end{aligned}} \right]\),\({{\bf{u}}_{\bf{3}}} = \left[ {\begin{aligned}{\bf{1}}\\{\bf{1}}\\{ - {\bf{2}}}\\{ - {\bf{1}}}\end{aligned}} \right]\),\({{\bf{u}}_{\bf{4}}} = \left[ {\begin{aligned}{ - {\bf{1}}}\\{\bf{1}}\\{\bf{1}}\\{ - {\bf{2}}}\end{aligned}} \right]\),\({\bf{x}} = \left[ {\begin{aligned}{\bf{4}}\\{\bf{5}}\\{ - {\bf{3}}}\\{\bf{3}}\end{aligned}} \right]\)

Write v as the sum of two vectors, one in\({\bf{Span}}\left\{ {{{\bf{u}}_1}} \right\}\)and the other in\({\bf{Span}}\left\{ {{{\bf{u}}_2},{{\bf{u}}_3},{{\bf{u}}_{\bf{4}}}} \right\}\).

In exercises 1-6, determine which sets of vectors are orthogonal.

\(\left[ {\begin{array}{*{20}{c}}3\\{-2}\\1\\3\end{array}} \right]\), \(\left[ {\begin{array}{*{20}{c}}{-1}\\3\\{-3}\\4\end{array}} \right]\), \(\left[ {\begin{array}{*{20}{c}}3\\8\\7\\0\end{array}} \right]\)

a. Rewrite the data in Example 1 with new \(x\)-coordinates in mean deviation form. Let \(X\) be the associated design matrix. Why are the columns of \(X\) orthogonal?

b. Write the normal equations for the data in part (a), and solve them to find the least-squares line, \(y = {\beta _0} + {\beta _1}x*\), where \(x* = x - 5.5\).

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