SPECIFICATION AND ESTIMATION OF LOGICALLY CONSISTENT LINEAR MODELS
研究了线性模型中因变量和自变量受约束时对参数的影响，提出模型参数满足多面体约束可保证因变量预测值一致，并定义了“逻辑一致”模型。
The implications of constrained dependent and independent variables for model parameters are examined. In the context of linear model systems, it is shown that polyhedral constraints on the dependent variables will hold over the domain of the independent variables when a set of polyhedral constraints is satisfied by the model parameters. This result may be used in parameter estimation, in which case all predicted values of the dependent variables are consistent with constraints on the actual values. Also, the implicit constraints that define the set of parameters for many commonly used linear stochastic models with an error term yield values of the dependent variables consistent with the explicit constraints. Models possessing these properties are termed “logically consistent”.