In this article, the true model of sizep is considered. The importance of the independent variables will be studied. The model by dropping independent variable one at a time is called a reduced model, and the size of ...In this article, the true model of sizep is considered. The importance of the independent variables will be studied. The model by dropping independent variable one at a time is called a reduced model, and the size of the model is p-1. The non-centrality quantity is employed to measure the strength of influence on the true model for the independent variable dropped. The larger influence is defined to be more important in the true model. In this article, the goal is ranking the importance of the independent variables to study the structure of the models. It is important in the practical application. The confidence interval approach is used to rank the degrees of the influence of the independent variables in linear models and achieve the goal. An illustrative example is given, and the modeling procedure is studied to check the assumptions step by step in this example to make sure the assumptions satisfied in the true model. As a result, the proposed method can be used efficiently.展开更多
文摘In this article, the true model of sizep is considered. The importance of the independent variables will be studied. The model by dropping independent variable one at a time is called a reduced model, and the size of the model is p-1. The non-centrality quantity is employed to measure the strength of influence on the true model for the independent variable dropped. The larger influence is defined to be more important in the true model. In this article, the goal is ranking the importance of the independent variables to study the structure of the models. It is important in the practical application. The confidence interval approach is used to rank the degrees of the influence of the independent variables in linear models and achieve the goal. An illustrative example is given, and the modeling procedure is studied to check the assumptions step by step in this example to make sure the assumptions satisfied in the true model. As a result, the proposed method can be used efficiently.
