BibTex RIS Cite

An Information-Theoretic Alternative to Maximum Likelihood Estimation Method in Ultrastructural Measurement Error Model 

Year 2011, Volume: 40 Issue: 3, 469 - 481, 01.03.2011

References

  • 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,
  • On-line book: http://www.mtm.ufsc.br/˜taneja/book/book.html, 2001.
  • Tsallis, C. Possible generalization of Boltzmann-Gibbs statistics, J. Statistical Physics 52, 479–487, 1988.

An Information-Theoretic Alternative to Maximum Likelihood Estimation Method in Ultrastructural Measurement Error Model 

Year 2011, Volume: 40 Issue: 3, 469 - 481, 01.03.2011

References

  • 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,
  • On-line book: http://www.mtm.ufsc.br/˜taneja/book/book.html, 2001.
  • Tsallis, C. Possible generalization of Boltzmann-Gibbs statistics, J. Statistical Physics 52, 479–487, 1988.
There are 28 citations in total.

Details

Primary Language Turkish
Journal Section Mathematics
Authors

Amjad D. Al-nasser This is me

Publication Date March 1, 2011
Published in Issue Year 2011 Volume: 40 Issue: 3

Cite

APA 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. March 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, no. 3 (March 2011): 469-81.
EndNote Al-nasser AD (March 1, 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, vol. 40, no. 3, pp. 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 (March 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, vol. 40, no. 3, 2011, pp. 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.