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SPECIFICATION AND ESTIMATION OF LOGICALLY CONSISTENT LINEAR MODELS
Author(s) -
Koehler Gary J.,
Wildt Albert R.
Publication year - 1981
Publication title -
decision sciences
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.238
H-Index - 108
eISSN - 1540-5915
pISSN - 0011-7315
DOI - 10.1111/j.1540-5915.1981.tb00056.x
Subject(s) - context (archaeology) , set (abstract data type) , mathematics , variables , mathematical optimization , estimation , errors in variables models , computer science , linear model , econometrics , statistics , paleontology , biology , programming language , management , economics
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”.