Template:Response Surface Explanation - Revision history

Admin at 21:47, 13 July 2011

2011-07-13T21:47:02Z

← Older revision		Revision as of 21:47, 13 July 2011
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	See the Matlab <code>regstats()</code> help page for more information: http://www.mathworks.com/help/toolbox/stats/regstats.html		See the Matlab <code>regstats()</code> help page for more information: http://www.mathworks.com/help/toolbox/stats/regstats.html

			Example of how to use this information to compute the value of a response surface is here: [[EvaluateResponseSurface.m]]

Admin: moved Template:Resopnse Surface Explanation to Template:Response Surface Explanation

2011-07-13T21:43:44Z

moved Template:Resopnse Surface Explanation to Template:Response Surface Explanation

← Older revision	Revision as of 21:43, 13 July 2011
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Admin at 21:43, 13 July 2011

2011-07-13T21:43:25Z

← Older revision		Revision as of 21:43, 13 July 2011
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	* <code>response_surface</code>		* <code>response_surface</code>
	** cell object that results from Matlab's <code>regstats()</code> function		** cell object that results from Matlab's <code>regstats()</code> function
	** polynomial coefficients corresponding to each row of <~~math~~>model</code> object are contained in <code>response_surface.beta</code>		** polynomial coefficients corresponding to each row of <code>model</code> object are contained in <code>response_surface.beta</code>
	** covariance matrix is stored in <code>response_surface.covb</code>		** covariance matrix is stored in <code>response_surface.covb</code>
	** R-squared and adjusted R-squared values stored in <code>response_surface.rsquare</code> and <code>response_surface.adjrsquare</code>, respectively		** R-squared and adjusted R-squared values stored in <code>response_surface.rsquare</code> and <code>response_surface.adjrsquare</code>, respectively

Admin: Created page with "Once you download the .mat file associated with a response surface, you will see two variables: * `model` ** matrix of size $N_{vars} \times N_{polynomial terms}..."$

2011-07-13T21:42:54Z

Created page with "Once you download the .mat file associated with a response surface, you will see two variables: * <code>model</code> ** matrix of size <math>N_{vars} \times N_{polynomial terms}..."

New page

Once you download the .mat file associated with a response surface, you will see two variables:

* <code>model</code>
** matrix of size <math>N_{vars} \times N_{polynomial terms}</math>
** number of columns is equal to the number of input variables <math>N_{vars}</math>
** number of rows is equal to the number of terms in the polynomial response surface <math>N_{polynomial terms}</math>
** variable order is as follows:
*** Mass flowrate <math>\dot{m}</math>
*** Reaction rate <math>k(T)</math>
*** Mixing length <math>L_{mix}</math>
*** Measurement location 1 <math>z_1</math>
*** Measurement location 2 <math>z_2</math>
*** Measurement location 3 <math>z_3</math>

* <code>response_surface</code>
** cell object that results from Matlab's <code>regstats()</code> function
** polynomial coefficients corresponding to each row of <math>model</code> object are contained in <code>response_surface.beta</code>
** covariance matrix is stored in <code>response_surface.covb</code>
** R-squared and adjusted R-squared values stored in <code>response_surface.rsquare</code> and <code>response_surface.adjrsquare</code>, respectively
** mean square error is contained in <code>response_surface.mse</code>

See the Matlab <code>regstats()</code> help page for more information: http://www.mathworks.com/help/toolbox/stats/regstats.html

Template:Response Surface Explanation - Revision history

Admin at 21:47, 13 July 2011

Admin: moved Template:Resopnse Surface Explanation to Template:Response Surface Explanation

Admin at 21:43, 13 July 2011

Admin: Created page with "Once you download the .mat file associated with a response surface, you will see two variables: * model ** matrix of size N_{vars} \times N_{polynomial terms}..."

Admin: Created page with "Once you download the .mat file associated with a response surface, you will see two variables: * `model` ** matrix of size $N_{vars} \times N_{polynomial terms}..."$