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Marian Grendar

Personal Details

First Name:Marian
Middle Name:
Last Name:Grendar
Suffix:
RePEc Short-ID:pgr53
http://www.savbb.sk/~grendar
Dept. of Mathematics, Bel University Tajovskeho 40 974 01 Banska Bystrica Slovakia

Research output

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Jump to: Working papers Articles

Working papers

  1. Marian Grendar Jr & Marian Grendar, 2003. "Maximum Probability/Entropy translating of contiguous categorical observations into frequencies," Econometrics 0309003, University Library of Munich, Germany.

Articles

  1. Grendár, M., 2012. "Is the p-value a good measure of evidence? Asymptotic consistency criteria," Statistics & Probability Letters, Elsevier, vol. 82(6), pages 1116-1119.
  2. Marian Grendar & George Judge, 2008. "Large-Deviations Theory and Empirical Estimator Choice," Econometric Reviews, Taylor & Francis Journals, vol. 27(4-6), pages 513-525.
  3. Grendar, Marian & Judge, George & Schechter, Laura, 2007. "An empirical non-parametric likelihood family of data-based Benford-like distributions," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 380(C), pages 429-438.

Citations

Many of the citations below have been collected in an experimental project, CitEc, where a more detailed citation analysis can be found. These are citations from works listed in RePEc that could be analyzed mechanically. So far, only a minority of all works could be analyzed. See under "Corrections" how you can help improve the citation analysis.

Working papers

  1. Marian Grendar Jr & Marian Grendar, 2003. "Maximum Probability/Entropy translating of contiguous categorical observations into frequencies," Econometrics 0309003, University Library of Munich, Germany.

    Cited by:

    1. Grendar, Marian & Judge, George G., 2006. "Large Deviations Theory and Empirical Estimator Choice," CUDARE Working Papers 25084, University of California, Berkeley, Department of Agricultural and Resource Economics.

Articles

  1. Grendár, M., 2012. "Is the p-value a good measure of evidence? Asymptotic consistency criteria," Statistics & Probability Letters, Elsevier, vol. 82(6), pages 1116-1119.

    Cited by:

    1. Shuai Luo & Hongyue Sun & Qingyun Ping & Ran Jin & Zhen He, 2016. "A Review of Modeling Bioelectrochemical Systems: Engineering and Statistical Aspects," Energies, MDPI, vol. 9(2), pages 1-27, February.

  2. Grendar, Marian & Judge, George & Schechter, Laura, 2007. "An empirical non-parametric likelihood family of data-based Benford-like distributions," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 380(C), pages 429-438.

    Cited by:

    1. Villas-Boas, Sofia B. & Fu, Qiuzi & Judge, George, 2017. "Benford’s law and the FSD distribution of economic behavioral micro data," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 486(C), pages 711-719.
    2. Lee, Joanne & Cho, Wendy K. Tam & Judge, George G., 2010. "Stigler's approach to recovering the distribution of first significant digits in natural data sets," Statistics & Probability Letters, Elsevier, vol. 80(2), pages 82-88, January.
    3. George Judge & Laura Schechter, 2009. "Detecting Problems in Survey Data Using Benford’s Law," Journal of Human Resources, University of Wisconsin Press, vol. 44(1).
    4. Villas-Boas, Sofia & Fu, Qiuzi & Judge, George, 2015. "Is Benford's Law a Universal Behavioral Theory?," Department of Agricultural & Resource Economics, UC Berkeley, Working Paper Series qt6x45h2fw, Department of Agricultural & Resource Economics, UC Berkeley.
    5. Lee, Joanne & Judge, George G., 2008. "Identifying falsified clinical data," CUDARE Working Papers 47001, University of California, Berkeley, Department of Agricultural and Resource Economics.
    6. Paul Hofmarcher & Kurt Hornik, 2013. "First Significant Digits and the Credit Derivative Market During the Financial Crisis," Contemporary Economics, University of Economics and Human Sciences in Warsaw., vol. 7(2), June.
    7. Morrow, John, 2014. "Benford's Law, families of distributions and a test basis," LSE Research Online Documents on Economics 60364, London School of Economics and Political Science, LSE Library.

More information

Research fields, statistics, top rankings, if available.

Statistics

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Co-authorship network on CollEc

NEP Fields

NEP is an announcement service for new working papers, with a weekly report in each of many fields. This author has had 1 paper announced in NEP. These are the fields, ordered by number of announcements, along with their dates. If the author is listed in the directory of specialists for this field, a link is also provided.
  1. NEP-ECM: Econometrics (1) 2003-09-14

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