Advanced Engineering Mathematics
Advanced Engineering Mathematics
10th Edition
ISBN: 9780470458365
Author: Erwin Kreyszig
Publisher: Wiley, John & Sons, Incorporated
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### Fitting a Cubic Trend Function

#### Problem Statement:
Fit a cubic trend function to the given data points: \[ (-2, 6), (-1, 8), (0, 8), (1, 7), (2, 6) \]

#### Definitions:
Let the polynomial functions be defined as:
\[ p_0(t) = 1 \]
\[ p_1(t) = t \]
\[ p_2(t) = t^2 - 2 \]

The orthogonal cubic polynomial is defined as:
\[ p_3(t) = \frac{5}{6}t^3 - \frac{17}{6}t \]

#### Explanation:
To fit the cubic trend function, we use these orthogonal polynomials and their associated vectors:

For \( p_0, p_1, \) and \( p_2 \), the vectors are:
\[ p_0 \rightarrow 
\begin{pmatrix}
1 \\
1 \\
1 \\
1 \\
1
\end{pmatrix}
\]

\[ p_1 \rightarrow 
\begin{pmatrix}
-2 \\
-1 \\
0 \\
1 \\
2
\end{pmatrix}
\]

\[ p_2 \rightarrow 
\begin{pmatrix}
-1 \\
-1 \\
0 \\
1 \\
2
\end{pmatrix}
\]

#### Objective:
To find and express the cubic trend function \(\hat{p}(t)\), incorporating the given data points and orthogonal polynomials.

\[ \hat{p}(t) = \boxed{} \]

This expression involves determining the coefficients that best fit the respective orthogonal polynomials to the given data set.
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Transcribed Image Text:### Fitting a Cubic Trend Function #### Problem Statement: Fit a cubic trend function to the given data points: \[ (-2, 6), (-1, 8), (0, 8), (1, 7), (2, 6) \] #### Definitions: Let the polynomial functions be defined as: \[ p_0(t) = 1 \] \[ p_1(t) = t \] \[ p_2(t) = t^2 - 2 \] The orthogonal cubic polynomial is defined as: \[ p_3(t) = \frac{5}{6}t^3 - \frac{17}{6}t \] #### Explanation: To fit the cubic trend function, we use these orthogonal polynomials and their associated vectors: For \( p_0, p_1, \) and \( p_2 \), the vectors are: \[ p_0 \rightarrow \begin{pmatrix} 1 \\ 1 \\ 1 \\ 1 \\ 1 \end{pmatrix} \] \[ p_1 \rightarrow \begin{pmatrix} -2 \\ -1 \\ 0 \\ 1 \\ 2 \end{pmatrix} \] \[ p_2 \rightarrow \begin{pmatrix} -1 \\ -1 \\ 0 \\ 1 \\ 2 \end{pmatrix} \] #### Objective: To find and express the cubic trend function \(\hat{p}(t)\), incorporating the given data points and orthogonal polynomials. \[ \hat{p}(t) = \boxed{} \] This expression involves determining the coefficients that best fit the respective orthogonal polynomials to the given data set.
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