Selected publications and presentations




Grendár, M., and Špitalský, V., Multinomial and empirical likelihood under convex constraints: directions of recession, Fenchel duality, perturbations. arXiv.1408.5621, Aug 2014.  Supplementary information can be found here.
                                                   Peer-reviewed offspring:
                                                   Grendár, Marian; Špitalský, Vladimír. Multinomial and empirical likelihood under convex constraints: Directions of recession, Fenchel duality, the PP algorithm. Electron. J. Statist. 11 (2017), no. 1, 2547-2612.

Grendár, M., Majerová, J. and Špitalský, V., Strong laws for recurrence quantification analysis, Int. J. Bifurcation Chaos, 23, 1350147,  2013.  doi: 10.1142/S0218127413501472

Špitalský, V. and Grendár, M., OPTICS-based clustering of emails represented by quantitative profiles. In DCAI, Advances in Intelligent Systems and Computing, Vol. 217, pp. 53-60, 2013.

Grendár, M. and Judge, G.,  Not all empirical divergence minimizing statistical methods are created equal? In ICNPAA 2012, S. Sivasundaram (ed.), AIP (Melville), pp. 432-435, 2012.

Grendár, M. and Judge, G., Contrasting revised empirical likelihood and its competitors, MESA, 3(4), 357-366, 2012.

Grendár, M., Škutová, J. and Špitalský, V., Email categorization and spam filtering by random forest with new classes of quantitative profiles. In Compstat 2012, A. Colubi et al. (eds).

Grendár, M., Škutová, J. and Špitalský, V., Spam filtering by quantitative profiles, arXiv.1201.0040v1 [cs.IR], Dec 2011. Supplementary material, including documented R code and data, can be found here.

Grendar, M.,  Is the p-value a good measure of evidence? An asymptotic consistency criterion,  arXiv:1111.4821v1 [math.ST],  Nov 2011. Presentation.
                      Peer-reviewed offspring:
                      Grendar, M.,  Is the p-value a good measure of evidence? Asymptotic consistency criteriaStatis. Probab. Lett., 82, 1116-1119, 2012.

Grendar, M. and Judge, G.,  Large deviations theory and econometric information recovery.  In Handbook of empirical economics and finance, A.Ullah and D. E. A. Giles (eds.), pp. 155-182, Chapman & Hall/CRC, 2011.

Grendar, M. and Judge, G., Revised Empirical Likelihood. CUDARE working paper 1106. Jul 2010.

Grendar, M., Empirical Likelihood. A talk at Robust 2010.

Grendar, M. and Judge, G., Maximum Likelihood with Estimating Equations. CUDARE working paper 1094. Jan 2010.
                                           Corrected (Feb 8, 2010), corrections at Sect. 1

Grendar, M. and Judge, G., Maximum Empirical Likelihood: Empty Set Problem. CUDARE working paper 1090. Sep 2009.
                               Peer-reviewed offspring:
                               M. Grendar and G. Judge, Empty set problem of maximum empirical likelihood methodsElectron. J. Statist., 3, 1542-1555, 2009.

Grendar, M. and Judge, G., Asymptotic Equivalence of Empirical Likelihood and Bayesian MAP, Ann. Statist., 37(5A), pp. 2445-2457, 2009.

Grendar, M., Maximum Probability and Relative Entropy Maximization. Bayesian Maximum Probability and Empirical Likelihood, Proc. of Intnl. Workshop on Applied Probability, France, 2008. Presentation .

Grendar, M., Judge, G. and Schechter, L., An empirical non-parametric likelihood family of data-based Benford-like distributions. Physica A, 380, 429-438, 2007.

Grendar, M., Dewar dice (Maximum Probability and Maximum Entropy Production), Dec. 2007.

Ramer, A., Grendar, M. and Padet, C., Graph Entropy and Conditioning, poster at Facets of Entropy workshop, Copenhagen, Oct. 2007.

Grendar, M., Maximum Probability, Maximum Entropy and Empirical Likelihood (Probabilistic regularization of inverse problems), a survey, June 2007.

Grendar, M. and R. K. Niven, The Polya Urn: Limit Theorems, Polya Divergence, Maximum Entropy and Maximum Probability, 2006.
                                 Peer-reviewed offsprings:
                                 1) R. K. Niven and M. Grendar, Generalized classical, quantum and intermediate statistics and the Pólya urn model,
                                 Phys. Lett. A, 373/6, 621-626, 2009.
                                 2) M. Grendar and R. K. Niven, The Polya Information Divergence, Inform. Sciences, 180/21, 4189-4194, 2010. Correction.
                         
   
Grendar, M., Boltzmann Jaynes Inverse Problem, Maximum Entropy and Maximum Probability, a presentation at Robert Niven's workshop, Canberra, Sep. 2006.

Grendar, M., Conditional Equi-concentration of Types, in Focus on Probability Theory, L. R. Velle (ed.), NSP (NY), pp. 73-89, 2006.

Grendar, M., Empirical Maximum Entropy Methods, in Bayesian inference and maximum entropy methods in science and engineering, A. Mohammad-Djafari (ed.), AIP (Melville), pp. 419-424, 2006.

Grendar, M. and Judge, G., Large Deviations Theory and Empirical Estimator Choice, Econometric Reviews, 27 (4-6), pp. 513-525, 2008. (Submitted in 2006).

Grendar, M., L-divergence consistency for a discrete prior, Jour. Stat. Research, 40[1], pp. 73-76, 2006.

Grendar, M., Entropy and Effective Support Size, Entropy, 8[3], pp. 169-174, 2006.

Grendar, M., Conditioning by rare sources, Acta Univ. M. Belii Math., 12, pp. 19-29, 2005.

Grendar, M., Jr. and Grendar, M., Maximum Probability/Entropy translating of contiguous categorical observations into frequencies, Appl. Math. Comp., 161, (2005), 347-351.

Grendar, M., Asymptotic identity of mu-projections and I-projections, Acta Univ. M. Belii Math., 11, pp. 3-6, 2004.

Grendar, M., Gibbs conditioning extended, Boltzmann conditioning introduced, in Bayesian inference and maximum entropy methods in science and engineering, R. Fischer, R. Preuss and U. von Toussaint (eds.), AIP (Melville), pp. 470-477, 2004.

Grendar, M., Determination of constrained modes of a multinomial distribution, Compstat 2004, J. Antoch (ed.), Physica, pp. 1109-1115, 2004.

Grendar, M., Jr. and Grendar, M., Maximum Probability and Maximum Entropy methods: Bayesian interpretation, in Bayesian inference and maximum entropy methods in science and engineering, G. Erickson and Y. Zhai (eds.), AIP (Melville), pp. 490-494, 2004.

Grendar, M., Jr. and Grendar, M., Maximum entropy method with non-linear moment constraints: challenges, in Bayesian inference and maximum entropy methods in science and engineering, G. Erickson and Y. Zhai (eds.), AIP (Melville), pp. 97-109, 2004.

Grendar, M., Jr. and Grendar, M., Chernoff's bound forms, in Bayesian inference and maximum entropy methods in science and engineering, Ch. Williams (ed.), AIP (Melville), pp. 67-72, 2003.

Grendar, M., Jr. and Grendar, M., Asymptotic Equiprobability of I-projections, Acta Univ. M Belii Math, 10, pp. 3-8, 2003.

Grendar, M., Jr. and Grendar, M., Randomness as an equilibrium. Potential and probability density, in Bayesian inference and maximum entropy methods in science and engineering, R. L. Fry (ed.), AIP (Melville), pp. 405-410, 2002.

Grendar, M. and Grendar, M., Jr., Why Maximum Entropy? A non-axiomatic approach, in Bayesian inference and maximum entropy methods in science and engineering, R. L. Fry (ed.), AIP (Melville), pp. 375-279, 2002.

Grendar, M., Jr. and Grendar, M., Maximum Entropy: clearing up mysteries, Entropy, 3, pp. 58-63, 2001.

Grendar, M., Jr. and Grendar, M., MiniMax Entropy and Maximum Likelihood: complementarity of tasks, identity of solutions, in Bayesian inference and maximum entropy methods in science and engineering, A. Mohammad-Djafari (ed.), AIP (Melville), pp. 49-61, 2001.

Grendar, M., Jr. and Grendar, M., What is the question that MaxEnt answers? A probabilistic interpretation, in Bayesian inference and maximum entropy methods in science and engineering, A. Mohammad-Djafari (ed.), AIP (Melville), pp. 83-94, 2001.

Grendar, M., Jr. and Grendar, M., On the probabilistic justification of I-divergence and J-divergence minimization, presented at Information Thoery in Mathematics, Balatonlelle (Hungary), July 2000.



Most of the papers are in preprint or postprint form available from arXiv or from other places.


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