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Evdokia Xekalaki

Personal Details

First Name:Evdokia
Middle Name:
Last Name:Xekalaki
Suffix:
RePEc Short-ID:pxe2
[This author has chosen not to make the email address public]
http://stat-athens.aueb.gr/~exek/

Affiliation

Athens University of Economics and Business (AUEB)

Athens, Greece
http://www.aueb.gr/
RePEc:edi:auebugr (more details at EDIRC)

Research output

as
Jump to: Working papers Articles

Working papers

  1. Xekalaki, Evdokia & Degiannakis, Stavros, 2005. "Evaluating Volatility Forecasts in Option Pricing in the Context of a Simulated Options Market," MPRA Paper 80468, University Library of Munich, Germany.
  2. Perakis, Michael & Maravelakis, Petros & Psarakis, Stelios & Xekalaki, Evdokia & Panaretos, John, 2005. "On Certain Indices for Ordinal Data with Unequally Weighted Classes," MPRA Paper 6395, University Library of Munich, Germany.
  3. Degiannakis, Stavros & Xekalaki, Evdokia, 2005. "Predictability and Model Selection in the Context of ARCH Models," MPRA Paper 80486, University Library of Munich, Germany.
  4. Panaretos, John & Psarakis, Stelios & Xekalaki, Evdokia & Karlis, Dimitris, 2005. "The Correlated Gamma-Ratio Distribution in Model Evaluation and Selection," MPRA Paper 6355, University Library of Munich, Germany.
  5. Degiannakis, Stavros & Xekalaki, Evdokia, 2004. "Autoregressive Conditional Heteroskedasticity (ARCH) Models: A Review," MPRA Paper 80487, University Library of Munich, Germany.
  6. Xekalaki, Evdokia & Panaretos, John, 2004. "A Binomial Distribution With Dependent Trials And Its Use in Stochastic Model Evaluation," MPRA Paper 6393, University Library of Munich, Germany.
  7. Xekalaki, Evdokia & Panaretos, John & Psarakis, Stelios, 2003. "A Predictive Model Evaluation and Selection Approach - The Correlated Gamma Ratio Distribution," MPRA Paper 6389, University Library of Munich, Germany.
  8. Panaretos, John & Psarakis, Stelios & Xekalaki, Evdokia, 1998. "On a Distribution Arising in the Context of Comparative Model Performance Evaluation Problems," MPRA Paper 6276, University Library of Munich, Germany.
  9. Xekalaki, Evdokia & Panaretos, John, 1995. "Replenishing Stock Under Uncertainty," MPRA Paper 6261, University Library of Munich, Germany.
  10. Panaretos, John & Xekalaki, Evdokia, 1989. "A Probability Distribution Associated With Events With Multiple Occurrences," MPRA Paper 6253, University Library of Munich, Germany.
  11. Xekalaki, Evdokia & Panaretos, John, 1989. "On Some Distributions Arising in Inverse Cluster Sampling," MPRA Paper 6252, University Library of Munich, Germany.
  12. Panaretos, John & Xekalaki, Evdokia, 1986. "On Some Distributions Arising from Certain Generalized Sampling Schemes," MPRA Paper 6249, University Library of Munich, Germany.
  13. Panaretos, John & Xekalaki, Evdokia, 1986. "On Generalized Binomial and Multinomial Distributions and Their Relation to Generalized Poisson Distributions," MPRA Paper 6248, University Library of Munich, Germany.
  14. Panaretos, John & Xekalaki, Evdokia, 1986. "The Stuttering Generalized Waring Distribution," MPRA Paper 6250, University Library of Munich, Germany.
  15. Xekalaki, Evdokia & Panaretos, John, 1983. "Identifiability of Compound Poisson Distributions," MPRA Paper 6244, University Library of Munich, Germany.
  16. Xekalaki, Evdokia & Panaretos, John, 1979. "Characterization of the Compound Poisson Distribution," MPRA Paper 6221, University Library of Munich, Germany.

Articles

  1. M. Perakis & P. Maravelakis & S. Psarakis & E. Xekalaki & J. Panaretos, 2005. "On Certain Indices for Ordinal Data with Unequally Weighted Classes," Quality & Quantity: International Journal of Methodology, Springer, vol. 39(5), pages 515-536, October.
  2. Xekalaki, Evdokia & Degiannakis, Stavros, 2005. "Evaluating volatility forecasts in option pricing in the context of a simulated options market," Computational Statistics & Data Analysis, Elsevier, vol. 49(2), pages 611-629, April.
  3. Evdokia Xekalaki, 2005. "Letter to the Editor; Comments on the paper of Shan et al.: The multivariate Waring distribution," Scientometrics, Springer;Akadémiai Kiadó, vol. 62(2), pages 293-296, January.
  4. Karlis, Dimitris & Xekalaki, Evdokia, 2003. "Choosing initial values for the EM algorithm for finite mixtures," Computational Statistics & Data Analysis, Elsevier, vol. 41(3-4), pages 577-590, January.
  5. Dimitris Karlis & Evdokia Xekalaki, 1999. "On Testing for the Number of Components in a Mixed Poisson Model," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 51(1), pages 149-162, March.
  6. Karlis, Dimitris & Xekalaki, Evdokia, 1998. "Minimum Hellinger distance estimation for Poisson mixtures," Computational Statistics & Data Analysis, Elsevier, vol. 29(1), pages 81-103, November.
  7. Caterina Dimaki & Evdokia Xekalaki, 1996. "Towards a unification of certain characterizations by conditional expectations," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 48(1), pages 157-168, March.
  8. Panaretos, John & Xekalaki, Evdokia, 1989. "A probability distribution associated with events with multiple occurrences," Statistics & Probability Letters, Elsevier, vol. 8(4), pages 389-395, September.
  9. Panaretos, John & Xekalaki, Evdokia, 1986. "The stuttering generalized waring distribution," Statistics & Probability Letters, Elsevier, vol. 4(6), pages 313-318, October.
  10. Xekalaki, Evdokia, 1984. "Linear regression and the Yule distribution," Journal of Econometrics, Elsevier, vol. 24(3), pages 397-403, March.
    RePEc:taf:apfelt:v:3:y:2007:i:1:p:31-37 is not listed on IDEAS
    RePEc:taf:apfiec:v:17:y:2007:i:2:p:149-171 is not listed on IDEAS
    RePEc:taf:apfelt:v:4:y:2008:i:6:p:419-423 is not listed on IDEAS

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. Xekalaki, Evdokia & Degiannakis, Stavros, 2005. "Evaluating Volatility Forecasts in Option Pricing in the Context of a Simulated Options Market," MPRA Paper 80468, University Library of Munich, Germany.

    Cited by:

    1. Miazhynskaia, Tatiana & Fruhwirth-Schnatter, Sylvia & Dorffner, Georg, 2006. "Bayesian testing for non-linearity in volatility modeling," Computational Statistics & Data Analysis, Elsevier, vol. 51(3), pages 2029-2042, December.
    2. Degiannakis, Stavros & Xekalaki, Evdokia, 2007. "Assessing the Performance of a Prediction Error Criterion Model Selection Algorithm in the Context of ARCH Models," MPRA Paper 96324, University Library of Munich, Germany.
    3. Stavros Degiannakis & Evdokia Xekalaki, 2007. "Simulated evidence on the distribution of the standardized one-step-ahead prediction errors in ARCH processes," Applied Financial Economics Letters, Taylor & Francis Journals, vol. 3(1), pages 31-37.
    4. Vasilios Sogiakas, 2017. "Option trading for optimizing volatility forecasting," Journal of Statistical and Econometric Methods, SCIENPRESS Ltd, vol. 6(3), pages 1-3.
    5. Stavros Degiannakis & Alexandra Livada, 2016. "Evaluation of realized volatility predictions from models with leptokurtically and asymmetrically distributed forecast errors," Journal of Applied Statistics, Taylor & Francis Journals, vol. 43(5), pages 871-892, April.
    6. Degiannakis, Stavros, 2017. "The one-trading-day-ahead forecast errors of intra-day realized volatility," Research in International Business and Finance, Elsevier, vol. 42(C), pages 1298-1314.
    7. Angelidis, Timotheos & Degiannakis, Stavros, 2008. "Volatility forecasting: intra-day vs. inter-day models," MPRA Paper 80434, University Library of Munich, Germany.
    8. Degiannakis, Stavros & Filis, George, 2017. "Forecasting oil price realized volatility using information channels from other asset classes," MPRA Paper 96276, University Library of Munich, Germany.
    9. Stavros Degiannakis & Evdokia Xekalaki, 2008. "SPEC model selection algorithm for ARCH models: an options pricing evaluation framework," Applied Financial Economics Letters, Taylor & Francis Journals, vol. 4(6), pages 419-423.
    10. Andrada-Félix, Julián & Fernández-Rodríguez, Fernando & Fuertes, Ana-Maria, 2016. "Combining nearest neighbor predictions and model-based predictions of realized variance: Does it pay?," International Journal of Forecasting, Elsevier, vol. 32(3), pages 695-715.
    11. Degiannakis, Stavros, 2018. "Multiple Days Ahead Realized Volatility Forecasting: Single, Combined and Average Forecasts," MPRA Paper 96272, University Library of Munich, Germany.
    12. Borovkova, Svetlana & Permana, Ferry J., 2009. "Implied volatility in oil markets," Computational Statistics & Data Analysis, Elsevier, vol. 53(6), pages 2022-2039, April.
    13. Angelidis, Timotheos & Degiannakis, Stavros, 2008. "Volatility forecasting: Intra-day versus inter-day models," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 18(5), pages 449-465, December.
    14. Ane, Thierry, 2006. "An analysis of the flexibility of Asymmetric Power GARCH models," Computational Statistics & Data Analysis, Elsevier, vol. 51(2), pages 1293-1311, November.

  2. Perakis, Michael & Maravelakis, Petros & Psarakis, Stelios & Xekalaki, Evdokia & Panaretos, John, 2005. "On Certain Indices for Ordinal Data with Unequally Weighted Classes," MPRA Paper 6395, University Library of Munich, Germany.

    Cited by:

    1. André Fonseca & Vera Zina & Gonçalo Duarte & Francisca C. Aguiar & Patricia María Rodríguez-González & Maria Teresa Ferreira & Maria Rosário Fernandes, 2021. "Riparian Ecological Infrastructures: Potential for Biodiversity-Related Ecosystem Services in Mediterranean Human-Dominated Landscapes," Sustainability, MDPI, vol. 13(19), pages 1-21, September.

  3. Degiannakis, Stavros & Xekalaki, Evdokia, 2005. "Predictability and Model Selection in the Context of ARCH Models," MPRA Paper 80486, University Library of Munich, Germany.

    Cited by:

    1. Xekalaki, Evdokia & Degiannakis, Stavros, 2005. "Evaluating volatility forecasts in option pricing in the context of a simulated options market," Computational Statistics & Data Analysis, Elsevier, vol. 49(2), pages 611-629, April.
    2. Degiannakis, Stavros & Xekalaki, Evdokia, 2007. "Assessing the Performance of a Prediction Error Criterion Model Selection Algorithm in the Context of ARCH Models," MPRA Paper 96324, University Library of Munich, Germany.
    3. Stavros Degiannakis & Evdokia Xekalaki, 2007. "Simulated evidence on the distribution of the standardized one-step-ahead prediction errors in ARCH processes," Applied Financial Economics Letters, Taylor & Francis Journals, vol. 3(1), pages 31-37.
    4. Stavros Degiannakis & Alexandra Livada, 2016. "Evaluation of realized volatility predictions from models with leptokurtically and asymmetrically distributed forecast errors," Journal of Applied Statistics, Taylor & Francis Journals, vol. 43(5), pages 871-892, April.
    5. Degiannakis, Stavros, 2017. "The one-trading-day-ahead forecast errors of intra-day realized volatility," Research in International Business and Finance, Elsevier, vol. 42(C), pages 1298-1314.
    6. Stavros Degiannakis & Evdokia Xekalaki, 2008. "SPEC model selection algorithm for ARCH models: an options pricing evaluation framework," Applied Financial Economics Letters, Taylor & Francis Journals, vol. 4(6), pages 419-423.
    7. Degiannakis, Stavros, 2018. "Multiple Days Ahead Realized Volatility Forecasting: Single, Combined and Average Forecasts," MPRA Paper 96272, University Library of Munich, Germany.

  4. Panaretos, John & Psarakis, Stelios & Xekalaki, Evdokia & Karlis, Dimitris, 2005. "The Correlated Gamma-Ratio Distribution in Model Evaluation and Selection," MPRA Paper 6355, University Library of Munich, Germany.

    Cited by:

    1. Panaretos, John & Psarakis, Stelios & Xekalaki, Evdokia, 1998. "On a Distribution Arising in the Context of Comparative Model Performance Evaluation Problems," MPRA Paper 6276, University Library of Munich, Germany.
    2. Xekalaki, Evdokia & Panaretos, John & Psarakis, Stelios, 2003. "A Predictive Model Evaluation and Selection Approach - The Correlated Gamma Ratio Distribution," MPRA Paper 6389, University Library of Munich, Germany.

  5. Degiannakis, Stavros & Xekalaki, Evdokia, 2004. "Autoregressive Conditional Heteroskedasticity (ARCH) Models: A Review," MPRA Paper 80487, University Library of Munich, Germany.

    Cited by:

    1. Tim Bollerslev, 2008. "Glossary to ARCH (GARCH)," CREATES Research Papers 2008-49, Department of Economics and Business Economics, Aarhus University.
    2. Xekalaki, Evdokia & Degiannakis, Stavros, 2005. "Evaluating volatility forecasts in option pricing in the context of a simulated options market," Computational Statistics & Data Analysis, Elsevier, vol. 49(2), pages 611-629, April.
    3. Angelidis, Timotheos & Degiannakis, Stavros, 2005. "Modeling Risk for Long and Short Trading Positions," MPRA Paper 80467, University Library of Munich, Germany.
    4. Degiannakis, Stavros & Xekalaki, Evdokia, 2007. "Assessing the Performance of a Prediction Error Criterion Model Selection Algorithm in the Context of ARCH Models," MPRA Paper 96324, University Library of Munich, Germany.
    5. Stavros Degiannakis & Evdokia Xekalaki, 2007. "Simulated evidence on the distribution of the standardized one-step-ahead prediction errors in ARCH processes," Applied Financial Economics Letters, Taylor & Francis Journals, vol. 3(1), pages 31-37.
    6. Willy Alanya & Gabriel Rodríguez, 2019. "Asymmetries in Volatility: An Empirical Study for the Peruvian Stock and Forex Markets," Review of Pacific Basin Financial Markets and Policies (RPBFMP), World Scientific Publishing Co. Pte. Ltd., vol. 22(01), pages 1-18, March.
    7. Remzi Uctum & Patricia Renou‐Maissant & Georges Prat & Sylvie Lecarpentier‐Moyal, 2017. "Persistence of announcement effects on the intraday volatility of stock returns: Evidence from individual data," Review of Financial Economics, John Wiley & Sons, vol. 35(1), pages 43-56, November.
    8. Wen Cheong, Chin & Hassan Shaari Mohd Nor, Abu & Isa, Zaidi, 2007. "Asymmetry and long-memory volatility: Some empirical evidence using GARCH," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 373(C), pages 651-664.
    9. Willy Alanya & Gabriel Rodríguez, 2018. "Stochastic Volatility in the Peruvian Stock Market and Exchange Rate Returns: A Bayesian Approximation," Journal of Emerging Market Finance, Institute for Financial Management and Research, vol. 17(3), pages 354-385, December.
    10. Stavros Degiannakis & Evdokia Xekalaki, 2005. "Predictability and model selection in the context of ARCH models," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 21(1), pages 55-82, January.
    11. Degiannakis, Stavros, 2004. "Volatility Forecasting: Evidence from a Fractional Integrated Asymmetric Power ARCH Skewed-t Model," MPRA Paper 96330, University Library of Munich, Germany.
    12. Degiannakis, Stavros & Livada, Alexandra & Panas, Epaminondas, 2008. "Rolling-sampled parameters of ARCH and Levy-stable models," MPRA Paper 80464, University Library of Munich, Germany.
    13. Emenike, Kalu O., 2018. "Stock Market Volatility Clustering and Asymmetry in Africa: A Post Global Financial Crisis Evidence," MPRA Paper 91653, University Library of Munich, Germany.
    14. Degiannakis, Stavros, 2004. "Forecasting Realized Intra-day Volatility and Value at Risk: Evidence from a Fractional Integrated Asymmetric Power ARCH Skewed-t Model," MPRA Paper 80488, University Library of Munich, Germany.
    15. Angelidis, Timotheos & Benos, Alexandros & Degiannakis, Stavros, 2004. "The Use of GARCH Models in VaR Estimation," MPRA Paper 96332, University Library of Munich, Germany.
    16. Saker Sabkha & Christian de Peretti, 2022. "On the performances of Dynamic Conditional Correlation models in the Sovereign CDS market and the corresponding bond market," Post-Print hal-01710398, HAL.
    17. Maghyereh Aktham Issa & Awartani Basel, 2012. "Modeling and Forecasting Value-at-Risk in the UAE Stock Markets: The Role of Long Memory, Fat Tails and Asymmetries in Return Innovations," Review of Middle East Economics and Finance, De Gruyter, vol. 8(1), pages 1-22, August.
    18. Sylvie Lecarpentier-Moyal & Georges Prat & Patricia Renou-Maissant & Remzi Uctum, 2013. "Persistence of announcement effects on the intraday volatility of stock returns: evidence from individual data," Working Papers hal-04141172, HAL.
    19. Hashem Zarafat & Sascha Liebhardt & Mustafa Hakan Eratalay, 2022. "Do ESG Ratings Reduce the Asymmetry Behavior in Volatility?," JRFM, MDPI, vol. 15(8), pages 1-32, July.

  6. Xekalaki, Evdokia & Panaretos, John & Psarakis, Stelios, 2003. "A Predictive Model Evaluation and Selection Approach - The Correlated Gamma Ratio Distribution," MPRA Paper 6389, University Library of Munich, Germany.

    Cited by:

    1. Xekalaki, Evdokia & Degiannakis, Stavros, 2005. "Evaluating volatility forecasts in option pricing in the context of a simulated options market," Computational Statistics & Data Analysis, Elsevier, vol. 49(2), pages 611-629, April.
    2. Degiannakis, Stavros & Xekalaki, Evdokia, 2007. "Assessing the Performance of a Prediction Error Criterion Model Selection Algorithm in the Context of ARCH Models," MPRA Paper 96324, University Library of Munich, Germany.
    3. Vasilios Sogiakas, 2017. "Option trading for optimizing volatility forecasting," Journal of Statistical and Econometric Methods, SCIENPRESS Ltd, vol. 6(3), pages 1-3.
    4. Stavros Degiannakis & Evdokia Xekalaki, 2005. "Predictability and model selection in the context of ARCH models," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 21(1), pages 55-82, January.
    5. Xekalaki, Evdokia & Panaretos, John, 2004. "A Binomial Distribution With Dependent Trials And Its Use in Stochastic Model Evaluation," MPRA Paper 6393, University Library of Munich, Germany.

  7. Panaretos, John & Xekalaki, Evdokia, 1989. "A Probability Distribution Associated With Events With Multiple Occurrences," MPRA Paper 6253, University Library of Munich, Germany.

    Cited by:

    1. Anant Godbole & Stavros Papastavridis & Robert Weishaar, 1997. "Formulae and Recursions for the Joint Distribution of Success Runs of Several Lengths," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 49(1), pages 141-153, March.

  8. Xekalaki, Evdokia & Panaretos, John, 1989. "On Some Distributions Arising in Inverse Cluster Sampling," MPRA Paper 6252, University Library of Munich, Germany.

    Cited by:

    1. C. Satheesh Kumar & A. Riyaz, 2015. "A zero-inflated logarithmic series distribution of order k and its applications," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 99(1), pages 31-43, January.

  9. Panaretos, John & Xekalaki, Evdokia, 1986. "On Some Distributions Arising from Certain Generalized Sampling Schemes," MPRA Paper 6249, University Library of Munich, Germany.

    Cited by:

    1. C. Satheesh Kumar & A. Riyaz, 2015. "A zero-inflated logarithmic series distribution of order k and its applications," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 99(1), pages 31-43, January.
    2. C. Satheesh Kumar & A. Riyaz, 2016. "An order version of the alternative zero-inflated logarithmic series distribution and its applications," Journal of Applied Statistics, Taylor & Francis Journals, vol. 43(14), pages 2681-2695, October.
    3. Sigeo Aki, 2012. "Statistical modeling for discrete patterns in a sequence of exchangeable trials," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 64(3), pages 633-655, June.

  10. Panaretos, John & Xekalaki, Evdokia, 1986. "On Generalized Binomial and Multinomial Distributions and Their Relation to Generalized Poisson Distributions," MPRA Paper 6248, University Library of Munich, Germany.

    Cited by:

    1. Panaretos, John & Xekalaki, Evdokia, 1986. "The stuttering generalized waring distribution," Statistics & Probability Letters, Elsevier, vol. 4(6), pages 313-318, October.
    2. Panaretos, John & Xekalaki, Evdokia, 1989. "A probability distribution associated with events with multiple occurrences," Statistics & Probability Letters, Elsevier, vol. 8(4), pages 389-395, September.

  11. Panaretos, John & Xekalaki, Evdokia, 1986. "The Stuttering Generalized Waring Distribution," MPRA Paper 6250, University Library of Munich, Germany.

    Cited by:

    1. Wolfgang Glänzel, 2009. "The multi-dimensionality of journal impact," Scientometrics, Springer;Akadémiai Kiadó, vol. 78(2), pages 355-374, February.
    2. Gupta, Arjun K. & Nguyen, Truc T. & Wang, Yinning & Wesolowski, Jacek, 2001. "Identifiability of Modified Power Series Mixtures via Posterior Means," Journal of Multivariate Analysis, Elsevier, vol. 77(2), pages 163-174, May.
    3. Lin Zhang & Wolfgang Glänzel & Liming Liang, 2009. "Tracing the role of individual journals in a cross-citation network based on different indicators," Scientometrics, Springer;Akadémiai Kiadó, vol. 81(3), pages 821-838, December.
    4. Shi Shan & Guohua Jiang & Lan Jiang, 2004. "The multivariate Waring distribution and its application," Scientometrics, Springer;Akadémiai Kiadó, vol. 60(3), pages 523-535, August.
    5. Panaretos, John, 1989. "Some Properties and Applications of the Stuttering Generalized Waring Distribution," MPRA Paper 6256, University Library of Munich, Germany.
    6. Haab, T. C., 2003. "Temporal correlation in recreation demand models with limited data," Journal of Environmental Economics and Management, Elsevier, vol. 45(2), pages 195-212, March.
    7. Panaretos, John & Xekalaki, Evdokia, 1989. "A probability distribution associated with events with multiple occurrences," Statistics & Probability Letters, Elsevier, vol. 8(4), pages 389-395, September.
    8. Panaretos, John & Xekalaki, Evdokia, 1986. "On Some Distributions Arising from Certain Generalized Sampling Schemes," MPRA Paper 6249, University Library of Munich, Germany.
    9. Saras Sarasvathy & Anil Menon & Graciela Kuechle, 2013. "Failing firms and successful entrepreneurs: serial entrepreneurship as a temporal portfolio," Small Business Economics, Springer, vol. 40(2), pages 417-434, February.
    10. Kemp, Adrienne W., 2013. "New discrete Appell and Humbert distributions with relevance to bivariate accident data," Journal of Multivariate Analysis, Elsevier, vol. 113(C), pages 2-6.
    11. José Rodríguez-Avi & Antonio Conde-Sánchez & Antonio Sáez-Castillo & María Olmo-Jiménez, 2004. "A triparametric discrete distribution with complex parameters," Statistical Papers, Springer, vol. 45(1), pages 81-95, January.
    12. Xekalaki, Evdokia & Panaretos, John, 1983. "Identifiability of Compound Poisson Distributions," MPRA Paper 6244, University Library of Munich, Germany.
    13. Valentina Cueva-López & María José Olmo-Jiménez & José Rodríguez-Avi, 2021. "An Over and Underdispersed Biparametric Extension of the Waring Distribution," Mathematics, MDPI, vol. 9(2), pages 1-15, January.
    14. María Dolores Huete-Morales & Juan Antonio Marmolejo-Martín, 2020. "The Waring Distribution as a Low-Frequency Prediction Model: A Study of Organic Livestock Farms in Andalusia," Mathematics, MDPI, vol. 8(11), pages 1-11, November.

  12. Xekalaki, Evdokia & Panaretos, John, 1983. "Identifiability of Compound Poisson Distributions," MPRA Paper 6244, University Library of Munich, Germany.

    Cited by:

    1. Panaretos, John & Xekalaki, Evdokia, 1986. "The stuttering generalized waring distribution," Statistics & Probability Letters, Elsevier, vol. 4(6), pages 313-318, October.
    2. Panaretos, John & Xekalaki, Evdokia, 1986. "On Generalized Binomial and Multinomial Distributions and Their Relation to Generalized Poisson Distributions," MPRA Paper 6248, University Library of Munich, Germany.

  13. Xekalaki, Evdokia & Panaretos, John, 1979. "Characterization of the Compound Poisson Distribution," MPRA Paper 6221, University Library of Munich, Germany.

    Cited by:

    1. Panaretos, John, 1981. "On the Joint Distribution of Two Discrete Random Variables," MPRA Paper 6226, University Library of Munich, Germany.
    2. Panaretos, John, 1982. "On a Structural Property of Finite Distributions," MPRA Paper 6242, University Library of Munich, Germany.

Articles

  1. M. Perakis & P. Maravelakis & S. Psarakis & E. Xekalaki & J. Panaretos, 2005. "On Certain Indices for Ordinal Data with Unequally Weighted Classes," Quality & Quantity: International Journal of Methodology, Springer, vol. 39(5), pages 515-536, October.
    See citations under working paper version above.
  2. Xekalaki, Evdokia & Degiannakis, Stavros, 2005. "Evaluating volatility forecasts in option pricing in the context of a simulated options market," Computational Statistics & Data Analysis, Elsevier, vol. 49(2), pages 611-629, April.
    See citations under working paper version above.
  3. Karlis, Dimitris & Xekalaki, Evdokia, 2003. "Choosing initial values for the EM algorithm for finite mixtures," Computational Statistics & Data Analysis, Elsevier, vol. 41(3-4), pages 577-590, January.

    Cited by:

    1. Antonio Punzo & Paul. D. McNicholas, 2017. "Robust Clustering in Regression Analysis via the Contaminated Gaussian Cluster-Weighted Model," Journal of Classification, Springer;The Classification Society, vol. 34(2), pages 249-293, July.
    2. Adrian O’Hagan & Arthur White, 2019. "Improved model-based clustering performance using Bayesian initialization averaging," Computational Statistics, Springer, vol. 34(1), pages 201-231, March.
    3. Andrews, Jeffrey L., 2018. "Addressing overfitting and underfitting in Gaussian model-based clustering," Computational Statistics & Data Analysis, Elsevier, vol. 127(C), pages 160-171.
    4. Maria Iannario, 2012. "Preliminary estimators for a mixture model of ordinal data," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 6(3), pages 163-184, October.
    5. Oh, Sebeom & Ku, Hyejin & Jun, Doobae, 2022. "A comparative analysis of housing prices in different cities using the Black–Scholes and Jump Diffusion models," Finance Research Letters, Elsevier, vol. 46(PA).
    6. Heather Shappell & Sean L. Simpson, 2022. "Discussion on “Distributional independent component analysis for diverse neuroimaging modalities” by Ben Wu, Subhadip Pal, Jian Kang, and Ying Guo," Biometrics, The International Biometric Society, vol. 78(3), pages 1106-1108, September.
    7. Jeremy T. Fox & Kyoo il Kim, 2011. "A Simple Nonparametric Approach to Estimating the Distribution of Random Coefficients in Structural Models," NBER Working Papers 17283, National Bureau of Economic Research, Inc.
    8. Nicolas Depraetere & Martina Vandebroek, 2014. "Order selection in finite mixtures of linear regressions," Statistical Papers, Springer, vol. 55(3), pages 871-911, August.
    9. Arielle Marks‐Anglin & Chongliang Luo & Jin Piao & Mary Beth Connolly Gibbons & Christopher H. Schmid & Jing Ning & Yong Chen, 2022. "EMBRACE: An EM‐based bias reduction approach through Copas‐model estimation for quantifying the evidence of selective publishing in network meta‐analysis," Biometrics, The International Biometric Society, vol. 78(2), pages 754-765, June.
    10. Gabriele Perrone & Gabriele Soffritti, 2023. "Seemingly unrelated clusterwise linear regression for contaminated data," Statistical Papers, Springer, vol. 64(3), pages 883-921, June.
    11. Wilfried Seidel & Hana Ševčíková, 2004. "Types of likelihood maxima in mixture models and their implication on the performance of tests," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 56(4), pages 631-654, December.
    12. Francesco Bartolucci & Giorgio E. Montanari & Silvia Pandolfi, 2018. "Latent Ignorability and Item Selection for Nursing Home Case-Mix Evaluation," Journal of Classification, Springer;The Classification Society, vol. 35(1), pages 172-193, April.
    13. Chuku Chuku & Paul Middleditch, 2020. "Characterizing Monetary and Fiscal Policy Rules and Interactions when Commodity Prices Matter," Manchester School, University of Manchester, vol. 88(3), pages 373-404, June.
    14. Francesco Bartolucci & Giorgio E. Montanari & Silvia Pandolfi, 2016. "Item selection by latent class-based methods: an application to nursing home evaluation," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 10(2), pages 245-262, June.
    15. Ker, Alan. P & Tolhurst, Tor & Liu, Yong, 2015. "Rating Area-yield Crop Insurance Contracts Using Bayesian Model Averaging and Mixture Models," 2015 AAEA & WAEA Joint Annual Meeting, July 26-28, San Francisco, California 205211, Agricultural and Applied Economics Association.
    16. Neal, Mark, 2007. "Estimating complex production functions: The importance of starting values," Risk and Sustainable Management Group Working Papers 151178, University of Queensland, School of Economics.
    17. Sahin, Özge & Czado, Claudia, 2022. "Vine copula mixture models and clustering for non-Gaussian data," Econometrics and Statistics, Elsevier, vol. 22(C), pages 136-158.
    18. Yoichi Miyata & Takayuki Shiohama & Toshihiro Abe, 2020. "Estimation of finite mixture models of skew-symmetric circular distributions," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 83(8), pages 895-922, November.
    19. O’Hagan, Adrian & Murphy, Thomas Brendan & Gormley, Isobel Claire, 2012. "Computational aspects of fitting mixture models via the expectation–maximization algorithm," Computational Statistics & Data Analysis, Elsevier, vol. 56(12), pages 3843-3864.
    20. Melnykov, Volodymyr & Melnykov, Igor, 2012. "Initializing the EM algorithm in Gaussian mixture models with an unknown number of components," Computational Statistics & Data Analysis, Elsevier, vol. 56(6), pages 1381-1395.
    21. Schücking, Maximilian & Jochem, Patrick, 2021. "Two-stage stochastic program optimizing the cost of electric vehicles in commercial fleets," Applied Energy, Elsevier, vol. 293(C).
    22. Saif Eddin Jabari & Nikolaos M. Freris & Deepthi Mary Dilip, 2020. "Sparse Travel Time Estimation from Streaming Data," Transportation Science, INFORMS, vol. 54(1), pages 1-20, January.
    23. Mahdi Teimouri & Saralees Nadarajah, 2022. "Maximum Likelihood Estimation for the Asymmetric Exponential Power Distribution," Computational Economics, Springer;Society for Computational Economics, vol. 60(2), pages 665-692, August.
    24. Pietro Coretto & Christian Hennig, 2010. "A simulation study to compare robust clustering methods based on mixtures," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 4(2), pages 111-135, September.
    25. Papastamoulis, Panagiotis & Martin-Magniette, Marie-Laure & Maugis-Rabusseau, Cathy, 2016. "On the estimation of mixtures of Poisson regression models with large number of components," Computational Statistics & Data Analysis, Elsevier, vol. 93(C), pages 97-106.
    26. Salvatore Ingrassia & Antonio Punzo & Giorgio Vittadini & Simona Minotti, 2015. "The Generalized Linear Mixed Cluster-Weighted Model," Journal of Classification, Springer;The Classification Society, vol. 32(1), pages 85-113, April.
    27. Antonello Maruotti & Antonio Punzo, 2021. "Initialization of Hidden Markov and Semi‐Markov Models: A Critical Evaluation of Several Strategies," International Statistical Review, International Statistical Institute, vol. 89(3), pages 447-480, December.
    28. Derek S. Young & Xi Chen & Dilrukshi C. Hewage & Ricardo Nilo-Poyanco, 2019. "Finite mixture-of-gamma distributions: estimation, inference, and model-based clustering," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 13(4), pages 1053-1082, December.
    29. Hung Tong & Cristina Tortora, 2022. "Model-based clustering and outlier detection with missing data," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 16(1), pages 5-30, March.
    30. Kerekes, Monika, 2012. "Growth miracles and failures in a Markov switching classification model of growth," Journal of Development Economics, Elsevier, vol. 98(2), pages 167-177.
    31. Salvatore Ingrassia & Antonio Punzo, 2020. "Cluster Validation for Mixtures of Regressions via the Total Sum of Squares Decomposition," Journal of Classification, Springer;The Classification Society, vol. 37(2), pages 526-547, July.
    32. Chun Yu & Weixin Yao & Guangren Yang, 2020. "A Selective Overview and Comparison of Robust Mixture Regression Estimators," International Statistical Review, International Statistical Institute, vol. 88(1), pages 176-202, April.
    33. Mai, Feng & Fry, Michael J. & Ohlmann, Jeffrey W., 2018. "Model-based capacitated clustering with posterior regularization," European Journal of Operational Research, Elsevier, vol. 271(2), pages 594-605.
    34. Angelo Mazza & Antonio Punzo, 2020. "Mixtures of multivariate contaminated normal regression models," Statistical Papers, Springer, vol. 61(2), pages 787-822, April.
    35. Ingo W Nader & Ulrich S Tran & Martin Voracek, 2015. "Effects of Initial Values and Convergence Criterion in the Two-Parameter Logistic Model When Estimating the Latent Distribution in BILOG-MG 3," PLOS ONE, Public Library of Science, vol. 10(10), pages 1-14, October.
    36. Morris, Katherine & Punzo, Antonio & McNicholas, Paul D. & Browne, Ryan P., 2019. "Asymmetric clusters and outliers: Mixtures of multivariate contaminated shifted asymmetric Laplace distributions," Computational Statistics & Data Analysis, Elsevier, vol. 132(C), pages 145-166.
    37. Tao, Jian & Shi, Ning-Zhong & Lee, S.-Y.Sik-Yum, 2004. "Drug risk assessment with determining the number of sub-populations under finite mixture normal models," Computational Statistics & Data Analysis, Elsevier, vol. 46(4), pages 661-676, July.
    38. Lin, Tsung-I & McLachlan, Geoffrey J. & Lee, Sharon X., 2016. "Extending mixtures of factor models using the restricted multivariate skew-normal distribution," Journal of Multivariate Analysis, Elsevier, vol. 143(C), pages 398-413.
    39. Ali Fadhaa & Zhang Jian, 2017. "Mixture model-based association analysis with case-control data in genome wide association studies," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 16(3), pages 173-187, August.
    40. Salvatore Ingrassia & Antonio Punzo & Giorgio Vittadini & Simona Minotti, 2015. "Erratum to: The Generalized Linear Mixed Cluster-Weighted Model," Journal of Classification, Springer;The Classification Society, vol. 32(2), pages 327-355, July.
    41. David L. Weakliem & Bradley R. Entner Wright, 2009. "Robustness of Group-Based Models for Longitudinal Count Data," Sociological Methods & Research, , vol. 38(1), pages 147-170, August.
    42. Paolo Berta & Salvatore Ingrassia & Antonio Punzo & Giorgio Vittadini, 2016. "Multilevel cluster-weighted models for the evaluation of hospitals," METRON, Springer;Sapienza Università di Roma, vol. 74(3), pages 275-292, December.
    43. Bartolucci, Francesco & Giorgio E., Montanari & Pandolfi, Silvia, 2012. "Item selection by an extended Latent Class model: An application to nursing homes evaluation," MPRA Paper 38757, University Library of Munich, Germany.
    44. Masahiro Kuroda & Zhi Geng & Michio Sakakihara, 2015. "Improving the vector $$\varepsilon $$ ε acceleration for the EM algorithm using a re-starting procedure," Computational Statistics, Springer, vol. 30(4), pages 1051-1077, December.
    45. Sharon Lee & Geoffrey McLachlan, 2013. "Model-based clustering and classification with non-normal mixture distributions," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 22(4), pages 427-454, November.
    46. Wan-Lun Wang & Luis M. Castro & Wan-Chen Hsieh & Tsung-I Lin, 2021. "Mixtures of factor analyzers with covariates for modeling multiply censored dependent variables," Statistical Papers, Springer, vol. 62(5), pages 2119-2145, October.
    47. Bohning, Dankmar & Seidel, Wilfried, 2003. "Editorial: recent developments in mixture models," Computational Statistics & Data Analysis, Elsevier, vol. 41(3-4), pages 349-357, January.
    48. Schücking, Maximilian & Jochem, Patrick, 2020. "Two-stage stochastic program optimizing the total cost of ownership of electric vehicles in commercial fleets," Working Paper Series in Production and Energy 50, Karlsruhe Institute of Technology (KIT), Institute for Industrial Production (IIP).
    49. Wan-Lun Wang & Tsung-I Lin, 2022. "Robust clustering of multiply censored data via mixtures of t factor analyzers," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 31(1), pages 22-53, March.
    50. Garel, Bernard, 2007. "Recent asymptotic results in testing for mixtures," Computational Statistics & Data Analysis, Elsevier, vol. 51(11), pages 5295-5304, July.
    51. Nicola Loperfido, 2019. "Finite mixtures, projection pursuit and tensor rank: a triangulation," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 13(1), pages 145-173, March.
    52. Manisera, Marica & Zuccolotto, Paola, 2022. "A mixture model for ordinal variables measured on semantic differential scales," Econometrics and Statistics, Elsevier, vol. 22(C), pages 98-123.
    53. Blostein, Martin & Miljkovic, Tatjana, 2019. "On modeling left-truncated loss data using mixtures of distributions," Insurance: Mathematics and Economics, Elsevier, vol. 85(C), pages 35-46.
    54. Patrick Bajari & Jeremy T. Fox & Kyoo il Kim & Stephen P. Ryan, 2009. "A Simple Nonparametric Estimator for the Distribution of Random Coefficients," NBER Working Papers 15210, National Bureau of Economic Research, Inc.
    55. Wraith, Darren & Forbes, Florence, 2015. "Location and scale mixtures of Gaussians with flexible tail behaviour: Properties, inference and application to multivariate clustering," Computational Statistics & Data Analysis, Elsevier, vol. 90(C), pages 61-73.
    56. Marcelo Coca Perraillon & Ya-Chen Tina Shih & Ronald A. Thisted, 2015. "Predicting the EQ-5D-3L Preference Index from the SF-12 Health Survey in a National US Sample," Medical Decision Making, , vol. 35(7), pages 888-901, October.
    57. Kerekes, Monika, 2009. "Growth miracles and failures in a Markov switching classification model of growth," Discussion Papers 2009/11, Free University Berlin, School of Business & Economics.

  4. Dimitris Karlis & Evdokia Xekalaki, 1999. "On Testing for the Number of Components in a Mixed Poisson Model," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 51(1), pages 149-162, March.

    Cited by:

    1. Karlis, Dimitris & Xekalaki, Evdokia, 2003. "Choosing initial values for the EM algorithm for finite mixtures," Computational Statistics & Data Analysis, Elsevier, vol. 41(3-4), pages 577-590, January.
    2. Umashanger, T. & Sriram, T.N., 2009. "L2E estimation of mixture complexity for count data," Computational Statistics & Data Analysis, Elsevier, vol. 53(12), pages 4243-4254, October.
    3. Schlattmann, Peter, 2003. "Estimating the number of components in a finite mixture model: the special case of homogeneity," Computational Statistics & Data Analysis, Elsevier, vol. 41(3-4), pages 441-451, January.
    4. Woo, Mi-Ja & Sriram, T.N., 2007. "Robust estimation of mixture complexity for count data," Computational Statistics & Data Analysis, Elsevier, vol. 51(9), pages 4379-4392, May.

  5. Karlis, Dimitris & Xekalaki, Evdokia, 1998. "Minimum Hellinger distance estimation for Poisson mixtures," Computational Statistics & Data Analysis, Elsevier, vol. 29(1), pages 81-103, November.

    Cited by:

    1. Wu, Jingjing & Karunamuni, Rohana J., 2012. "Efficient Hellinger distance estimates for semiparametric models," Journal of Multivariate Analysis, Elsevier, vol. 107(C), pages 1-23.
    2. Jingjing Wu & Tasnima Abedin & Qiang Zhao, 2023. "Semiparametric modelling of two-component mixtures with stochastic dominance," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 75(1), pages 39-70, February.
    3. Takada, Teruko, 2009. "Simulated minimum Hellinger distance estimation of stochastic volatility models," Computational Statistics & Data Analysis, Elsevier, vol. 53(6), pages 2390-2403, April.
    4. Liming Xiang & Kelvin K. W. Yau & Yer Van Hui & Andy H. Lee, 2008. "Minimum Hellinger Distance Estimation for k-Component Poisson Mixture with Random Effects," Biometrics, The International Biometric Society, vol. 64(2), pages 508-518, June.
    5. Derek S. Young & Xi Chen & Dilrukshi C. Hewage & Ricardo Nilo-Poyanco, 2019. "Finite mixture-of-gamma distributions: estimation, inference, and model-based clustering," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 13(4), pages 1053-1082, December.
    6. Wang, Yong, 2007. "Minimum disparity computation via the iteratively reweighted least integrated squares algorithms," Computational Statistics & Data Analysis, Elsevier, vol. 51(12), pages 5662-5672, August.
    7. Umashanger, T. & Sriram, T.N., 2009. "L2E estimation of mixture complexity for count data," Computational Statistics & Data Analysis, Elsevier, vol. 53(12), pages 4243-4254, October.
    8. Karunamuni, Rohana J. & Wu, Jingjing, 2011. "One-step minimum Hellinger distance estimation," Computational Statistics & Data Analysis, Elsevier, vol. 55(12), pages 3148-3164, December.
    9. Wooi Chen Khoo & Seng Huat Ong & Atanu Biswas, 2017. "Modeling time series of counts with a new class of INAR(1) model," Statistical Papers, Springer, vol. 58(2), pages 393-416, June.
    10. Tang, Qingguo & Karunamuni, Rohana J., 2013. "Minimum distance estimation in a finite mixture regression model," Journal of Multivariate Analysis, Elsevier, vol. 120(C), pages 185-204.
    11. Zudi Lu & Yer Van Hui & Andy H. Lee, 2003. "Minimum Hellinger Distance Estimation for Finite Mixtures of Poisson Regression Models and Its Applications," Biometrics, The International Biometric Society, vol. 59(4), pages 1016-1026, December.
    12. Chee, Chew-Seng, 2017. "A mixture model-based nonparametric approach to estimating a count distribution," Computational Statistics & Data Analysis, Elsevier, vol. 109(C), pages 34-44.
    13. Woo, Mi-Ja & Sriram, T.N., 2007. "Robust estimation of mixture complexity for count data," Computational Statistics & Data Analysis, Elsevier, vol. 51(9), pages 4379-4392, May.

  6. Caterina Dimaki & Evdokia Xekalaki, 1996. "Towards a unification of certain characterizations by conditional expectations," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 48(1), pages 157-168, March.

    Cited by:

    1. Arnold, Barry C. & Castillo, Enrique & Sarabia, Jose Maria, 2002. "Exact and near compatibility of discrete conditional distributions," Computational Statistics & Data Analysis, Elsevier, vol. 40(2), pages 231-252, August.
    2. Koski, Timo & Sandström, Erik & Sandström, Ulf, 2016. "Towards field-adjusted production: Estimating research productivity from a zero-truncated distribution," Journal of Informetrics, Elsevier, vol. 10(4), pages 1143-1152.

  7. Panaretos, John & Xekalaki, Evdokia, 1989. "A probability distribution associated with events with multiple occurrences," Statistics & Probability Letters, Elsevier, vol. 8(4), pages 389-395, September.
    See citations under working paper version above.
  8. Panaretos, John & Xekalaki, Evdokia, 1986. "The stuttering generalized waring distribution," Statistics & Probability Letters, Elsevier, vol. 4(6), pages 313-318, October.
    See citations under working paper version above.
  9. Xekalaki, Evdokia, 1984. "Linear regression and the Yule distribution," Journal of Econometrics, Elsevier, vol. 24(3), pages 397-403, March.

    Cited by:

    1. Saralees Nadarajah, 2009. "Models for over reported income," Applied Economics Letters, Taylor & Francis Journals, vol. 16(7), pages 699-703.
    2. Caterina Dimaki & Evdokia Xekalaki, 1996. "Towards a unification of certain characterizations by conditional expectations," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 48(1), pages 157-168, March.
    3. Xekalaki, Evdokia & Panaretos, John, 1995. "Replenishing Stock Under Uncertainty," MPRA Paper 6261, University Library of Munich, Germany.

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