Monte Carlo Response Surfaces: Difference between revisions
From charlesreid1
(Created page with "=Response Surface Results= ==Yp at exit== ===Quadratic Surface, 6 Dimensions=== Download the response surface here: http://files.charlesmartinreid.com/ExperimentalDesign/MCRes...") |
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=Response Surface Results= | =Response Surface Results= | ||
==Yp at X1== | |||
==Yp at X2== | |||
==Yp at X3== | |||
===Quadratic Surface, 6 Dimensions=== | |||
{{{ResponseSurface | |||
|link=http://files.charlesmartinreid.com/ExperimentalDesign/MCResponseSurface_Yp_x3_6dim_2deg.mat | |||
|comments1= | |||
|polynomial_coefficient_vector= | |||
|polynomial_powers_matrix= | |||
|comments2= | |||
|image= | |||
|comments3= | |||
|statistics= | |||
|comments4= | |||
|text= | |||
}}} | |||
==Yp at exit== | ==Yp at exit== | ||
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===Quadratic Surface, 6 Dimensions=== | ===Quadratic Surface, 6 Dimensions=== | ||
{{{ResponseSurface | |||
|link=http://files.charlesmartinreid.com/ExperimentalDesign/MCResponseSurface_Yp_exit_6dim_2deg.mat | |||
|comments1=A quadratic response surface was computed using all of the information from the Monte Carlo samples. There were 10,000 samples in total. | |||
<pre> | |polynomial_coefficient_vector=<pre> | ||
b(1) = 175.9 | b(1) = 175.9 | ||
b(2) = -55.47 | b(2) = -55.47 | ||
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</pre> | </pre> | ||
|polynomial_powers_matrix=<pre> | |||
<pre> | |||
0 0 0 0 0 0 | 0 0 0 0 0 0 | ||
0 0 0 0 0 1 | 0 0 0 0 0 1 | ||
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</pre> | </pre> | ||
|comments2= | |||
|image=MCResponseSurface_Yp_out_6dim_2deg.png | |||
|comments3= | |||
<pre> | |statistics=<pre> | ||
--------------------------------------------------- | --------------------------------------------------- | ||
Response surface summary of information: | Response surface summary of information: | ||
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</pre> | </pre> | ||
|comments4= | |||
|text= | |||
}}} | |||
===Quadratic Surface, 2 Dimensions=== | ===Quadratic Surface, 2 Dimensions=== | ||
{{{ResponseSurface | |||
|link=http://files.charlesmartinreid.com/ExperimentalDesign/MCResponseSurface_Yp_exit_2dim_2deg.mat | |||
The | |comments1=The same set of Monte Carlo samples was fit to a quadratic surface, but with 2 variables instead of 6. | ||
<pre> | |polynomial_coefficient_vector=<pre> | ||
b(1) = 0.2606 | b(1) = 0.2606 | ||
b(2) = -0.01793 | b(2) = -0.01793 | ||
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</pre> | </pre> | ||
|polynomial_powers_matrix=<pre> | |||
<pre> | |||
0 0 | 0 0 | ||
0 1 | 0 1 | ||
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</pre> | </pre> | ||
This results in a response surface that looks similar to the 6-dimensional quadratic response surface: | |comments2=This results in a response surface that looks similar to the 6-dimensional quadratic response surface: | ||
|image=MCResponseSurface_Yp_out_2dim_2deg.png | |||
The statistics show that the fit is better for the 2-dimensional surface than for the 6-dimensional surface. This, combined with the fact that he response surfaces look similar, means we can conclude that the additional dimensions are ''probably'' independent of the two visualized dimensions, or that they ave a minimal impact on the response. | |comments3=The statistics show that the fit is better for the 2-dimensional surface than for the 6-dimensional surface. This, combined with the fact that he response surfaces look similar, means we can conclude that the additional dimensions are ''probably'' independent of the two visualized dimensions, or that they ave a minimal impact on the response. | ||
<pre> | |statistics=<pre> | ||
--------------------------------------------------- | --------------------------------------------------- | ||
Response surface summary of information: | Response surface summary of information: | ||
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--------------------------------------------------- | --------------------------------------------------- | ||
</pre> | </pre> | ||
|comments4= | |||
|text= | |||
}}} | |||
===Cubic Surface, 6 Dimensions=== | ===Cubic Surface, 6 Dimensions=== | ||
{{{ResponseSurface | |||
|link=http://files.charlesmartinreid.com/ExperimentalDesign/MCResponseSurface_Yp_exit_6dim_3deg.mat | |||
|comments1= | |||
<pre> | |polynomial_coefficient_vector=<pre> | ||
b(1) = 9.4335e+04 | b(1) = 9.4335e+04 | ||
b(2) = -7.1360e+04 | b(2) = -7.1360e+04 | ||
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</pre> | </pre> | ||
|polynomial_powers_matrix=<pre> | |||
<pre> | |||
0 0 0 0 0 0 | 0 0 0 0 0 0 | ||
0 0 0 0 0 1 | 0 0 0 0 0 1 | ||
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</pre> | </pre> | ||
|comments2= | |||
|image=MCResponseSurface_Yp_exit_6dim_3deg.png | |||
|comments3= | |||
<pre> | |statistics=<pre> | ||
--------------------------------------------------- | --------------------------------------------------- | ||
Response surface summary of information: | Response surface summary of information: | ||
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</pre> | </pre> | ||
|comments4= | |||
|text= | |||
}}} | |||
===Quartic Response Surface=== | ===Quartic Response Surface=== | ||
{{{ResponseSurface | |||
|link=http://files.charlesmartinreid.com/ExperimentalDesign/MCResponseSurface_Yp_exit_6dim_4deg.mat | |||
|comments1=For the sake of brevity, the full coefficients and powers matrix won't be printed here (they are included in the response surface file above). | |||
|polynomial_coefficient_vector=(not included) | |||
<pre> | |polynomial_powers_matrix=(not included) | ||
|image=MCResponseSurface_Yp_out_6dim_4deg.png | |||
|statistics=<pre> | |||
--------------------------------------------------- | --------------------------------------------------- | ||
Response surface summary of information: | Response surface summary of information: | ||
| Line 396: | Line 431: | ||
</pre> | </pre> | ||
It is clear that despite having a high-degree polynomial with a large number (210) of coefficients, the polynomial fit is still quite poor, and increasing the degree of the polynomial does not greatly increase the polynomial's fit to the data. | |comments4=It is clear that despite having a high-degree polynomial with a large number (210) of coefficients, the polynomial fit is still quite poor, and increasing the degree of the polynomial does not greatly increase the polynomial's fit to the data. | ||
With the [[Composite Experimental Design#Computing Response Surface|composite design response surface]], the (reduced) third degree polynomial fit all of the data points exactly, and yielded 0 mean square error and an r-squared value of 1.0. However, this is because there were only 45 sample points, and almost as many polynomial coefficients - 37. | With the [[Composite Experimental Design#Computing Response Surface|composite design response surface]], the (reduced) third degree polynomial fit all of the data points exactly, and yielded 0 mean square error and an r-squared value of 1.0. However, this is because there were only 45 sample points, and almost as many polynomial coefficients - 37. | ||
}}} | |||
Revision as of 23:37, 3 July 2011
Response Surface Results
Yp at X1
Yp at X2
Yp at X3
Quadratic Surface, 6 Dimensions
link=http://files.charlesmartinreid.com/ExperimentalDesign/MCResponseSurface_Yp_x3_6dim_2deg.mat
Yp at exit
Quadratic Surface, 6 Dimensions
link=http://files.charlesmartinreid.com/ExperimentalDesign/MCResponseSurface_Yp_exit_6dim_2deg.mat
Quadratic Surface, 2 Dimensions
link=http://files.charlesmartinreid.com/ExperimentalDesign/MCResponseSurface_Yp_exit_2dim_2deg.mat
Cubic Surface, 6 Dimensions
link=http://files.charlesmartinreid.com/ExperimentalDesign/MCResponseSurface_Yp_exit_6dim_3deg.mat
Quartic Response Surface
link=http://files.charlesmartinreid.com/ExperimentalDesign/MCResponseSurface_Yp_exit_6dim_4deg.mat