This paper introduces the general multilevel models and discusses the generalized maximum entropy (GME) estimation method (Golan et al 1996) that may be used to fit such models. The proposed procedure is applied to two-level data generated in a simulation study. The GME estimates are compared with Goldstein’s generalized least squares estimates. The comparisons are made by two criteria, bias and efficiency. We find that the estimates of the fixed effects and variance components are substantially and significantly biased using Goldstein’s generalized Least Squares approach. However, the GME estimates are unbiased and consistent; we conclude that the GME approach is a recommended procedure to fit multilevel models
In this study we illustrate a Maximum Entropy (ME) methodology for modeling incomplete information a...
The concept and the mathematical properties of entropy play an im- portant role in statistics, cyber...
Continuing to emphasize numerical and graphical methods, An Introduction to Generalized Linear Model...
We introduce General Multilevel Models and discuss the estimation procedures that may be used to fit...
<p>In this article, we use the cross-entropy method for noisy optimization for fitting generalized l...
The generalized maximum entropy (GME) estimator was introduced by Golan et al. as a way to overcome ...
A generalized maximum entropy estimator is developed for the linear simultaneous equations systems m...
TEZ8812Tez (Yüksek Lisans) -- Çukurova Üniversitesi, Adana, 2012.Kaynakça (s. 56-61) var.xi, 62 s. :...
The method of Generalized Maximum Entropy (GME), proposed in Golan, Judge and Miller (1996), is an i...
Abstract: Consider the linear regression model y = X+ u in the usual notation. In many applications ...
This article deals with multiple linear functional relationships models. Two robust estimations proc...
The generalized maximum entropy method of information recovery requires that an analyst provides pri...
EnMoving Average process is a representation of a time series written as a finite linear combination...
Multicollinearity hampers empirical econometrics. The remedies proposed to date suffer from pitfall...
Multicollinearity hampers empirical econometrics. The remedies proposed to date suffer from pitfalls...
In this study we illustrate a Maximum Entropy (ME) methodology for modeling incomplete information a...
The concept and the mathematical properties of entropy play an im- portant role in statistics, cyber...
Continuing to emphasize numerical and graphical methods, An Introduction to Generalized Linear Model...
We introduce General Multilevel Models and discuss the estimation procedures that may be used to fit...
<p>In this article, we use the cross-entropy method for noisy optimization for fitting generalized l...
The generalized maximum entropy (GME) estimator was introduced by Golan et al. as a way to overcome ...
A generalized maximum entropy estimator is developed for the linear simultaneous equations systems m...
TEZ8812Tez (Yüksek Lisans) -- Çukurova Üniversitesi, Adana, 2012.Kaynakça (s. 56-61) var.xi, 62 s. :...
The method of Generalized Maximum Entropy (GME), proposed in Golan, Judge and Miller (1996), is an i...
Abstract: Consider the linear regression model y = X+ u in the usual notation. In many applications ...
This article deals with multiple linear functional relationships models. Two robust estimations proc...
The generalized maximum entropy method of information recovery requires that an analyst provides pri...
EnMoving Average process is a representation of a time series written as a finite linear combination...
Multicollinearity hampers empirical econometrics. The remedies proposed to date suffer from pitfall...
Multicollinearity hampers empirical econometrics. The remedies proposed to date suffer from pitfalls...
In this study we illustrate a Maximum Entropy (ME) methodology for modeling incomplete information a...
The concept and the mathematical properties of entropy play an im- portant role in statistics, cyber...
Continuing to emphasize numerical and graphical methods, An Introduction to Generalized Linear Model...