By Peter Englezos
A reference and textbook delivering readers with an important optimization equipment for parameter estimation in chemical engineering. The CD-ROM positive factors Fortran desktop courses for fixing equation structures and different issues of Microsoft Excel and Sigma Plot. comprises over 900 equations in all.
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Set the logical value Comt=true if you wish to calculate a y intercept value. Step 7. Step 8. Set the logical value Stats=true if you wish the program to return additional regression statistics. Step 9. Now that you have entered all the data you do not hit the OK button but instead press Control-Shift-Enter. This command allows all the elements in the array to be displayed. If you hit OK you will only see one element in the array. Once the above steps have been followed, the program returns the following information on the worksheet.
24) This problem corresponds to the multiple linear regression model with m=\, n=2 and/7=3. 19b become IN I*? Z"? 25b) Z*! The parameters estimates are now obtained from Copyright © 2001 by Taylor & Francis Group, LLC Computation of Parameters in Linear Models- Linear Regression 1 > 1> 31 IN Z"f Z-? Z"! 26) Z'? 27) This problem corresponds to the multiple linear regression model with m=\, n=3 and p=4. 19b become I. 28a) Z«f I"? N and x. 28b) Chapter 3 32 The parameters estimates are now obtained from N 1- -] k2 k3 >4.
J , I]1. 16 for the estimation of the parameters is not done by computing the inverse of matrix A. Instead, any good linear equation solver should be employed. Our preference is to perform first an eigenvalue decomposition of the real symmetric matrix A which provides significant additional information about potential ill-conditioning of the parameter estimation problem (see Chapter 8). 4 POLYNOMIAL CURVE FITTING In engineering practice we are often faced with the task of fitting a loworder polynomial curve to a set of data.
Applied Parameter Estimation for Chemical Engineers by Peter Englezos