The Analysis of Influence Factors of Single Box Consumption Based on the PLS Regression—From the Data of Tobacco Consumption Control in Honghe Cigarette Factory
Abstract: On the basis of some conditions for the application of partial least squares regression analysis and multivariate linear regression analysis in this paper, we can conclude that partial least squares regression (PLS) can effectively improve multicollinearity of variables. When the sample size is less than the number of variables, it also can be used to do regression modeling. Then, from 12 groups of sample data of Tobacco consumption control in Honghe Cigarette Factory, we have analyzed and compared the results of partial least squares regression modeling and multivariate linear regression modeling in the paper. It has shown that the significant factors affecting the single box consumption are single case of Wasting, single case of Running, single case of Packet rejection and single case of Short excluded volume. Therefore, the work of the cigarette factory in the process of reducing the cost should be firstly controlling these four single box loss indicators, so that we will achieve the immediate results.
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