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ECIV 301 Programming & Graphics Numerical Methods for Engineers Lecture 24 Regression Analysis-Chapter 17
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LAST TIME Splines
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Piecewise smooth polynomials
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LAST TIME E.G Quadratic Splines Function Values at adjacent polynomials are equal at interior nodes
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LAST TIME E.G Quadratic Splines First and Last Functions pass through end points
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LAST TIME E.G Quadratic Splines First Derivatives at Interior nodes are equal
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LAST TIME E.G Quadratic Splines Assume Second Derivative @ First Point=0
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LAST TIME E.G Quadratic Splines Assume Second Derivative @ First Point=0 Solve 3nx3n system of Equations
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LAST TIME Spline Interpolation Polynomial Interpolation Spline Interpolation Polynomial Interpolation
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Curve Fitting Often we are faced with the problem… what value of y corresponds to x=0.935?
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Curve Fitting Question 1 : Is it possible to find a simple and convenient formula that reproduces the points exactly? e.g. Straight Line ? …or smooth line ? …or some other representation? Interpolation
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Curve Fitting Question 2 : Is it possible to find a simple and convenient formula that represents data approximately ? e.g. Best Fit ? Approximation
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Experimental Measurements Strain Stress
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Experimental Measurements Strain Stress
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BEST FIT CRITERIA Strain y Stress Error at each Point Total Error
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Best Fit => Minimize Error Not a Good Choice Not a Unique Best Fit
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Best Fit => Minimize Error Try Absolute Not a Good Choice Not a Unique Best Fit
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Best Fit => Minimize Error Best Strategy
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Best Fit => Minimize Error Objective: What are the values of a o and a 1 that minimize ?
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Least Square Approximation What x minimizes f(x)? Remember:
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Least Square Approximation In our case Since x i and y i are known from given data
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Least Square Approximation
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2 Eqtns 2 Unknowns
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Least Square Approximation
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Example xyxyx2x2 10.5 1a1=0.839 22.554a0=0.0714 3269 4416 53.517.525 6636 75.538.549 2824119.5140
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Example
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