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Model control of mathematical models PDF Print E-mail
Written by Agnar Höskuldsson, DTU   
In the applied work with data we often formulate a mathematical model that is expected to be appropriate to the model. Data is used to estimate the unknown parameters in the model. The situation considered here is the case of regression analysis, where there are available data for the instrumental variables and the associated response values. Computing the response values and comparing those to the observed values of the response variables often present the quality of the model. Many papers that include applied data analysis only show as a result of the analysis a plot similar to Figure 1 and perhaps some plots involving score vectors. From an applied point of view this is not sufficient. There are different reasons for why these plots are not sufficient. The basic purpose of the mathematical modelling task is to provide with a model that gives good predictions. In order to arrive at such a model it is important to be aware of that the modelling task consists of two parts. This will be explained in terms of a linear regression model.
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