We discuss two methods for predicting outcomes using the discrete choice generalized maximum entr... more We discuss two methods for predicting outcomes using the discrete choice generalized maximum entropy (GME) estimator. Since the traditional GME formulation allows ŷ outside the [0,1] interval, we specify a new GME formulation, which requires 0≤ŷ≤1. We estimate a binary choice model to compare results between our GME estimator and the traditional GME estimator.
Journal of Statistical Computation and Simulation, 2006
In this paper, we propose a new way to impose parameter inequality constraints in a linear regres... more In this paper, we propose a new way to impose parameter inequality constraints in a linear regression model using the principle of maximum entropy. We describe the generalized maximum entropy (GME) estimator and develop a method for imposing parameter inequality restrictions through the traditional GME parameter support matrix. In addition, we develop a more general parameter support matrix that allows
We discuss two methods for predicting outcomes using the discrete choice generalized maximum entr... more We discuss two methods for predicting outcomes using the discrete choice generalized maximum entropy (GME) estimator. Since the traditional GME formulation allows ŷ outside the [0,1] interval, we specify a new GME formulation, which requires 0≤ŷ≤1. We estimate a binary choice model to compare results between our GME estimator and the traditional GME estimator.
Journal of Statistical Computation and Simulation, 2006
In this paper, we propose a new way to impose parameter inequality constraints in a linear regres... more In this paper, we propose a new way to impose parameter inequality constraints in a linear regression model using the principle of maximum entropy. We describe the generalized maximum entropy (GME) estimator and develop a method for imposing parameter inequality restrictions through the traditional GME parameter support matrix. In addition, we develop a more general parameter support matrix that allows
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Papers by Randall Campbell