Al-Nasser, A. Measuring Customer Satisfaction: An Information - Theoretic Approach (Lambert Academic Publishing AG & Co. KG., Germany, 2010).
Al-Nasser, A. Entropy type estimator to simple linear measurement error models, Austrian Journal of Statistics 34 (3), 283–294, 2005.
Al-Nasser, A. Estimation of multiple linear functional relationships, Journal of Modern Applied Statistical Methods 3 (1), 181–186, 2004.
Al-Nasser, A. Customer satisfaction measurement models: Generalized maximum entropy approach, Pakistan Journal of Statistics 19 (2), 213–226, 2003.
Caputo, M and Paris, Q. Comparative statics of the generalized maximum entropy estimator of the general linear model, European Journal of Operational Research 185 (1), 195–203, 2008.
Carroll, R. J., Ruppert, D. and Stefanski, L. A. Measurement Error in Nonlinear Models (Chapman and Hall, London, 1995).
Cheng, C. -L. and Van Ness, J. W. Statistical Regression with Measurement Error (Arlond, New York, 1999).
Ciavolino, E and Al-Nasser, A. Comparing generalized maximum entropy and partial least squares methods for structural equation models, Journal of Nonparametric Statistics 21 (8), 1017–1036, 2009.
Ciavolino, E and Dahlgaard, J. Simultaneous equation model based on the generalized max- imum entropy for studying the effect of management factors on enterprise performance, Journal of Applied Statistics 36 (7), 801–815, 2009
Csiszar, I. Why least squares and maximum entropy? An axiomatic approach to inference for linear inverse problems, The Annals of Statistics 19, 2032–2066, 1991.
Dolby, G. R. The ultra-structural model: A synthesis of the functional and structural rela- tions, Biometrika 63, 39–50, 1976.
Donho, D. L, Johnstone, I. M, Hoch, J. C, and Stern, A. S. Maximum entropy and nearly black object, J. Royal, Statistical Society, Ser B 54, 41–81, 1992.
Golan, A. Information and entropy econometrics - A review and synthesis, Foundations and Trends in Econometrics 2 (1-2), 1-145, 2008.
Golan, A., Judge, G. and Miller, D. A Maximum Entropy Econometrics: Robust Estimation with limited data(Wiley, New York, 1996).
Golan, A., Judge, G. and Perloff, J. Estimation and inference with censored and ordered multinomial response data, J. Econometrics 79, 23–51, 1997.
Gleser, L. J. A note on G. R. Dolby’s unreplicated ultrastructural model, Biometrika 72, 117–124, 1985.
Havrada, J. H. and Charvat, F. Quantification methods of classification process: Concept of structural α-entropy, Kybernetika 3, 30–35, 1967.
Jaynes, E. T. Information and Statistical Mechanics I, Physics Review 106, 620–630, 1957. [19] Jaynes, E. T. Information and Statistical Mechanics II, Physics Review 108, 171–190, 1957. [20] Jaynes, E. T. Information Theory and Statistical Mechanics, in Statistical Physics, K. Ford (ed.), (Benjamin, New York, 181, 1963).
Kapur J. N. Maximum Entropy Models in Science and Engineering (John Wiley & Sons, New York, 1989)
Paris, Q. Multicollinearity and maximum entropy estimators, Economics Bulletin 3 (11), 1–9, 2001.
Peeters, L. Estimating a random-coefficients sample-selection model using generalized max- imum entropy, Economics Letters 84, 87–92, 2004.
Pukelsheim, F. The three sigma rule, The American Statistician 48 (2), 88–91, 1994.
R´enyi, A. On measures of information and entropy (Proceedings of the 4th Berkeley Sym- posium on Mathematics, Statistics and Probability, 1960), 547–561, 1961.
Srivastava, A. and Shalabh, K. Consistent estimation for the non-normal ultrastructural model, Statist. Probab. Lett. 34, 67–73, 1997.
Shannon, C,E. A mathematical theory of communication, Bell System Technical Journal , 379–423, 1948. [28] Taneja,
I. J. Generalized Information Measures and Their Applications,
Al-Nasser, A. Measuring Customer Satisfaction: An Information - Theoretic Approach (Lambert Academic Publishing AG & Co. KG., Germany, 2010).
Al-Nasser, A. Entropy type estimator to simple linear measurement error models, Austrian Journal of Statistics 34 (3), 283–294, 2005.
Al-Nasser, A. Estimation of multiple linear functional relationships, Journal of Modern Applied Statistical Methods 3 (1), 181–186, 2004.
Al-Nasser, A. Customer satisfaction measurement models: Generalized maximum entropy approach, Pakistan Journal of Statistics 19 (2), 213–226, 2003.
Caputo, M and Paris, Q. Comparative statics of the generalized maximum entropy estimator of the general linear model, European Journal of Operational Research 185 (1), 195–203, 2008.
Carroll, R. J., Ruppert, D. and Stefanski, L. A. Measurement Error in Nonlinear Models (Chapman and Hall, London, 1995).
Cheng, C. -L. and Van Ness, J. W. Statistical Regression with Measurement Error (Arlond, New York, 1999).
Ciavolino, E and Al-Nasser, A. Comparing generalized maximum entropy and partial least squares methods for structural equation models, Journal of Nonparametric Statistics 21 (8), 1017–1036, 2009.
Ciavolino, E and Dahlgaard, J. Simultaneous equation model based on the generalized max- imum entropy for studying the effect of management factors on enterprise performance, Journal of Applied Statistics 36 (7), 801–815, 2009
Csiszar, I. Why least squares and maximum entropy? An axiomatic approach to inference for linear inverse problems, The Annals of Statistics 19, 2032–2066, 1991.
Dolby, G. R. The ultra-structural model: A synthesis of the functional and structural rela- tions, Biometrika 63, 39–50, 1976.
Donho, D. L, Johnstone, I. M, Hoch, J. C, and Stern, A. S. Maximum entropy and nearly black object, J. Royal, Statistical Society, Ser B 54, 41–81, 1992.
Golan, A. Information and entropy econometrics - A review and synthesis, Foundations and Trends in Econometrics 2 (1-2), 1-145, 2008.
Golan, A., Judge, G. and Miller, D. A Maximum Entropy Econometrics: Robust Estimation with limited data(Wiley, New York, 1996).
Golan, A., Judge, G. and Perloff, J. Estimation and inference with censored and ordered multinomial response data, J. Econometrics 79, 23–51, 1997.
Gleser, L. J. A note on G. R. Dolby’s unreplicated ultrastructural model, Biometrika 72, 117–124, 1985.
Havrada, J. H. and Charvat, F. Quantification methods of classification process: Concept of structural α-entropy, Kybernetika 3, 30–35, 1967.
Jaynes, E. T. Information and Statistical Mechanics I, Physics Review 106, 620–630, 1957. [19] Jaynes, E. T. Information and Statistical Mechanics II, Physics Review 108, 171–190, 1957. [20] Jaynes, E. T. Information Theory and Statistical Mechanics, in Statistical Physics, K. Ford (ed.), (Benjamin, New York, 181, 1963).
Kapur J. N. Maximum Entropy Models in Science and Engineering (John Wiley & Sons, New York, 1989)
Paris, Q. Multicollinearity and maximum entropy estimators, Economics Bulletin 3 (11), 1–9, 2001.
Peeters, L. Estimating a random-coefficients sample-selection model using generalized max- imum entropy, Economics Letters 84, 87–92, 2004.
Pukelsheim, F. The three sigma rule, The American Statistician 48 (2), 88–91, 1994.
R´enyi, A. On measures of information and entropy (Proceedings of the 4th Berkeley Sym- posium on Mathematics, Statistics and Probability, 1960), 547–561, 1961.
Srivastava, A. and Shalabh, K. Consistent estimation for the non-normal ultrastructural model, Statist. Probab. Lett. 34, 67–73, 1997.
Shannon, C,E. A mathematical theory of communication, Bell System Technical Journal , 379–423, 1948. [28] Taneja,
I. J. Generalized Information Measures and Their Applications,
Al-nasser, A. D. (2011). An Information-Theoretic Alternative to Maximum Likelihood Estimation Method in Ultrastructural Measurement Error Model . Hacettepe Journal of Mathematics and Statistics, 40(3), 469-481.
AMA
Al-nasser AD. An Information-Theoretic Alternative to Maximum Likelihood Estimation Method in Ultrastructural Measurement Error Model . Hacettepe Journal of Mathematics and Statistics. Mart 2011;40(3):469-481.
Chicago
Al-nasser, Amjad D. “An Information-Theoretic Alternative to Maximum Likelihood Estimation Method in Ultrastructural Measurement Error Model ”. Hacettepe Journal of Mathematics and Statistics 40, sy. 3 (Mart 2011): 469-81.
EndNote
Al-nasser AD (01 Mart 2011) An Information-Theoretic Alternative to Maximum Likelihood Estimation Method in Ultrastructural Measurement Error Model . Hacettepe Journal of Mathematics and Statistics 40 3 469–481.
IEEE
A. D. Al-nasser, “An Information-Theoretic Alternative to Maximum Likelihood Estimation Method in Ultrastructural Measurement Error Model ”, Hacettepe Journal of Mathematics and Statistics, c. 40, sy. 3, ss. 469–481, 2011.
ISNAD
Al-nasser, Amjad D. “An Information-Theoretic Alternative to Maximum Likelihood Estimation Method in Ultrastructural Measurement Error Model ”. Hacettepe Journal of Mathematics and Statistics 40/3 (Mart 2011), 469-481.
JAMA
Al-nasser AD. An Information-Theoretic Alternative to Maximum Likelihood Estimation Method in Ultrastructural Measurement Error Model . Hacettepe Journal of Mathematics and Statistics. 2011;40:469–481.
MLA
Al-nasser, Amjad D. “An Information-Theoretic Alternative to Maximum Likelihood Estimation Method in Ultrastructural Measurement Error Model ”. Hacettepe Journal of Mathematics and Statistics, c. 40, sy. 3, 2011, ss. 469-81.
Vancouver
Al-nasser AD. An Information-Theoretic Alternative to Maximum Likelihood Estimation Method in Ultrastructural Measurement Error Model . Hacettepe Journal of Mathematics and Statistics. 2011;40(3):469-81.